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In-vehicle human machine interfaces (HMI) represent a promising approach for informing drivers what they should do to adopt an eco-safe driving style, which is associated with reduced fuel consumption and improved safety. However, there is limited understanding of the driver acceptance of various types of in-vehicle HMIs and the impact of such systems on driving behaviour. Forty drivers participated in a simulated driving experiment to evaluate three variations of an eco-safe in-vehicle HMI: visual advice only; visual feedback only; or visual advice and feedback. To evaluate the impact of the different HMIs, subjective and objective measures were analysed, including fuel consumption, eco-safe driving behaviour, driver acceptance, and workload. Results indicate that all system types were associated with the relatively high levels of driver acceptance, with the advice only system accepted the most. While all system types produced relatively low levels of workload for drivers, systems involving feedback significantly increased the workload associated with using the interface. The findings suggest that the combined advice and feedback system has the potential to simultaneously reduce fuel consumption and improve eco-safe driving behaviour. Specifically, both advice and feedback appeared to be critical in encouraging positive changes in eco-safe driving behaviour. Our contribution can inform the design and development of future in-vehicle HMIs to improve eco-safe driving style that are accepted by drivers and have minimal adverse impacts on driver workload.

The emitting distributions of a hidden Markov model (HMM) are normally constructed using the cross moments of the process variables. Similar to the mean of a univariate probability distribution, the cross moment is the most fundamental statistic of a multivariate probability distribution, which is not capable of capturing the high-order statistical features of process data. To alleviate this limitation, the high-order equivalence of the cross moment demonstrated in this paper, as the complete dependence structure, is used to construct the emitting distribution for HMM. The complete dependence structure among the process variables is modeled in a Gaussian copula. A semiparametric data transformation is also proposed to ensure the necessary conditions for using a Gaussian copula are met. The final emitting distribution is constructed as a finite mixture of the copula models. The proposed HMM is tested on two industrial studies for performance validation. Note to Practitioners —Gaussian mixture model HMM (GMM-HMM) is an efficient and easy-to-implement tool for mode identification of dynamic industrial processes. These virtues of GMM-HMM mainly come from the use of Gaussian emitting distribution, which allows closed-form derivatives to be computed for the expectation and maximization (EM) estimation of mode parameters. The main novelty of the proposed copula mixture model HMM (SPCMM-HMM) is twofold; its emitting distribution also belongs to the exponential family, thus enabling efficient estimation of parameters through an exact EM procedure; meanwhile, it is also capable of characterizing complex dependence structures among process variables. However, the proposed SPCMM-HMM has more model parameters compared with the GMM-HMM. It excels in situations where the operation of the process system being monitored is highly integrated (with complex process variable interactions) and abundance of training data samples is available. In this paper, the interactions between process variables in both case studies are complex due to the implementation of multiple closed control loops, and a large amount of training data samples can be easily generated from simulation. The performance of the SPCMM-HMM is shown to be consistently better than that of the GMM-HMM under such settings, which are fairly common in modern industrial processes. Nonetheless, if the process system being considered is only designed for a simple operation or there is a scarcity of training data samples, the GMM-HMM is still the preferred method as it is less prone to overfitting.

Frequency Domain Spectroscopy (FDS) is proposed as a suitable diagnostic method in this paper for implementation on energized oil-paper insulation systems. In present FDS tests, the measurement method is only designed for offline applications. To overcome the deficiencies with the offline testing, this work investigates the feasibility of performing FDS measurements on energized transformers with the view to developing an online diagnostic tool using neutral connections as injection and measurement paths. In the proposed technique, a low-pass filter system is designed to remove the high frequency noise as well as the power frequency signals present in the measured neutral currents. The technique has been successfully applied in a laboratory environment on transformers with oil-paper insulation systems with different operational ages and is feasible for single-phase as well as 3-phase transformers with the accessible neutral points. Compared with the conventional FDS results, a nonlinear dielectric phenomenon is observed from the energized insulation systems as higher dissipation factor Tanδ values primarily due to the increased losses under power frequency voltage excitation. The degree of the nonlinearity is found to correlate well with the degradation status of insulation systems under test.

The data in this paper are related to the research articles entitled “Kinetics of transfemoral amputees with osseointegrated fixation performing common activities of daily living” (Lee et al., Clinical Biomechanics, 2007.22(6). p. 665–673) and “Magnitude and variability of loading on the osseointegrated implant of transfemoral amputees during walking” (Lee et al., Med Eng Phys, 2008.30(7). p. 825–833). This article contains the overall and individual loading characteristics applied on screw-type osseointegrated implant generated by transfemoral bone-anchored prostheses fitted with basic components during daily activities at self-selected comfortable pace. Overall and individual data was presented for the (A) spatio-temporal characteristics, (B) loading patterns, (C) loading boundaries and (D) the loading local extremum during level walking, ascending and descending ramp and stairs. Inter-participant variability of these new datasets with basic components is critical to improve the efficacy and safety of prosthetic components as well as the design of future automated algorithms and clinical trials. Online repository contains the files: https://data.mendeley.com/datasets/hh8rjjh73w/1. Keywords: Amputation, Artificial limb, Bone-anchored prosthesis (BAP), Direct skeletal attachment, Osseointegrated implants, Osseointegration, Prosthesis, Prosthetic knees, Prosthetic feet loading, Kinetics

Purpose The purpose of this paper is to examine current Australian e-conveyancing processes to identify its rewards and the risks requiring specific attention in order to protect consumers and ensure ongoing trust in the system. Design/methodology/approach Doctrinal legal research engaging with statutory and precedential case law; related policy documents and governmental agreements; academic and other related writings; news materials and Property Exchange of Australia documentation. Findings E-conveyancing rewards have received greater understanding than the inherent risks, which needs to be corrected by educating users and consumers. Originality/value The research adds to the academic literature in this emerging area of legal risk.

Much political, media and academic attention has focused on: (1) the legal test for evaluating whether there has been a breach of duty in the provision of innovative treatment; and (2) the extent to which the law reform proposed by Lord Saatchi in the Medical Innovation Bill (MIB) was necessary or desirable to relieve doctors of (perceived) legal strictures preventing innovative treatments. However, comparatively little attention has focused on the requirement that patients must provide consent to innovative treatment. In this paper we argue that the English and Australian law relating to consent is capable of application in the context of innovative treatment so as to provide certainty for health professionals and promote patient autonomy.

Hydropower is among the cleanest sources of energy. However, the rate of hydropower generation is profoundly affected by the inflow to the dam reservoirs. In this study, the Grey wolf optimization (GWO) method coupled with an adaptive neuro-fuzzy inference system (ANFIS) to forecast the hydropower generation. For this purpose, the Dez basin average of rainfall was calculated using Thiessen polygons. Twenty input combinations, including the inflow to the dam, the rainfall and the hydropower in the previous months were used, while the output in all the scenarios was one month of hydropower generation. Then, the coupled model was used to forecast the hydropower generation. Results indicated that the method was promising. GWO-ANFIS was capable of predicting the hydropower generation satisfactorily, while the ANFIS failed in nine input-output combinations.

Current state-of-the-art automatic speaker verification (ASV) systems are prone to spoofing. The security and reliability of ASV systems can be threatened by different types of spoofing attacks using voice conversion, synthetic speech, or recorded passphrase. It is therefore essential to develop countermeasure techniques which can detect such spoofed speech. Inspired by the success of deep learning approaches in various classification tasks, this work presents an in-depth study of convolutional neural networks (CNNs) for spoofing detection in automatic speaker verification (ASV) systems. Specifically, we have compared the use of three different CNNs architectures: AlexNet, CNNs with max-feature-map activation, and an ensemble of standard CNNs for developing spoofing countermeasures, and discussed their potential to avoid overfitting due to small amounts of training data that is usually available in this task. We used popular deep learning toolkits for the system implementation and have released the implementation code of our methods publicly. We have evaluated the proposed countermeasure systems for detecting replay attacks on recently released spoofing corpora ASVspoof 2017, and also provided in-depth visual analyses of CNNs to aid for future research in this area.

Introduction Rapid developments in transportation technologies, such as in-vehicle human-machine interfaces (HMI), have the potential to improve driving behaviour. However, the use of such approaches is typically voluntary and there are numerous barriers to their widespread implementation. The aim of the current paper is to evaluate the impact of monetary incentive combined with competition with other drivers on adoption and effectiveness of an eco-safe in-vehicle HMI. Moreover, this research assess intentions to use and willingness to purchase the in-vehicle HMI, both of which play crucial roles in sustained voluntary uptake of in-vehicle HMIs. Method Forty drivers participated in a driving simulator experiment and questionnaires. Three variations of an eco-safe driving in-vehicle HMI were evaluated (advice only, feedback only, combined advice and feedback), followed by an incentive-based condition. Results The findings revealed the 4.7% reduction in fuel consumption with an addition of incentive and competition with other drivers associated with the use of in-vehicle HMI on eco-safe driving behaviour. Moreover, there was some evidence to suggest that a range of extrinsic and intrinsic incentives may be beneficial for increasing intentions to use such a system. Conclusions We conclude that the addition of incentives may be more effective in encouraging greater intentions to use the in-vehicle HMI, compared to improving eco-safe driving behaviour associated with system use. Practical applications This research provides valuable knowledge towards enhancing the current understanding of the nature and features of eco-safe in vehicle HMIs. Such information provides a foundation for the design and development of novel in-vehicle systems, incorporating the influence of competition with other drivers and incentives to enhance the motivation to use in-vehicle systems and consequently, improve drivers’ fuel efficiency and safe driving behaviour.

The rapid development and growth of unmanned aerial vehicles (UAVs) as a remote sensing platform, as well as advances in the miniaturization of instrumentation and data systems, have resulted in an increasing uptake of this technology in the environmental and remote sensing science communities. Although tough regulations across the globe may still limit the broader use of UAVs, their use in precision agriculture, ecology, atmospheric research, disaster response biosecurity, ecological and reef monitoring, forestry, fire monitoring, quick response measurements for emergency disaster, Earth science research,volcanic gas sampling, monitoring of gas pipelines, mining plumes, humanitarian observations and biological/chemo-sensing tasks continues to increase. This Special Issue provides a forum for high-quality peer-reviewed papers that broaden the awareness and understanding of UAV developments, applications of UAVs for remote sensing, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities. This topic encompasses many algorithms and process flows and tools, including: robust vehicle detection in aerial images based on cascaded convolutional neural networks; a stereo dual-channel dynamic programming algorithm for UAV image stitching, as well as seamline determination based on PKGC segmentation for remote sensing image mosaicking; the implementation of an IMU-aided image stacking algorithm in digital cameras; the study of multispectral characteristics at different observation angles, rapid three-dimensional reconstruction for image sequence acquired from UAV cameras; comparisons of Riegl Ricopter UAV Lidar-derived canopy height and DBH with terrestrial Lidar; vision based target finding and inspection of a ground target using a multirotor UAV system; a localization framework for real-time UAV autonomous landing using an on-ground deployed visual approach; curvature continuous and bounded path planning for fixed-wing UAVs; the calculation and identification of the aerodynamic parameters for small-scaled fixed-wing UAVs Several wildfire and agricultural applications of UAVS including: deep learning-based wildfire identification in UAV imagery; postfire vegetation survey campaigns; secure utilization of beacons; and UAVS used in emergency response systems for building fire hazards; observing spring and fall phenology in a deciduous forest with aerial drone imagery; the design and testing of a UAV mapping system for agricultural field surveying; artificial neural network to predict vine water status spatial variability using multispectral information obtained from an unmanned aerial vehicle; automatic hotspot and sun glint detection in UAV multispectral images obtained via uncooled thermal camera calibration and optimization of the photogrammetry process for UAV applications in agriculture; olive yield forecast tool based on the tree canopy geometry using UAS imagery; spatial scale gap filling downscaling method for applications in precision agriculture; automatic co-registration algorithm to remove canopy shaded pixels in UAV-borne thermal images to improve the estimation of crop water stress on vineyards; methodologies for improving plant pest surveillance in vineyards and crops using UAV-based hyperspectral and spatial data; UAV-assisted dynamic clustering of wireless sensors and networks for crop health monitoring. Several applications of UAVS in the fields of environment and conservation including the following: the automatic detection of pre-existing termite mounds through UAS and hyperspectral imagery; aerial mapping of forests affected by pathogens using UAVs; hyperspectral sensors and artificial i ntelligence; coral reef and coral bleaching monitoring; invasive grass and vegetation surveys in remote arid lands. UAVs are also utilized in many other applications: vicarious calibration of SUAS microbolometer temperature imagery for the estimation of radiometric land surface temperature; the documentation of hiking trails in alpine areas; the detection of nuclear sources by UAV teleoperation using a visuo-haptic augmented reality interface; the design of a UAV-embedded microphone array system for sound source localization in outdoor environments; the monitoring of concentrated solar power plants, accuracy analysis of a dam model from drone surveys, mobile sensing and actuation infrastructure, UAV-based frameworks for river hydromorphological characterization; online aerial terrain mapping for ground robot navigation.

Research in information systems (IS) calls for increased validity of research findings through a rigorous research process. This research investigates the approach of researchers to suggested rigour criteria. Drawing upon existing literature on case study research methodology, we identify a set of criteria for establishing the rigour of a case study research. A coding scheme is developed based on these criteria. Our overarching proposition is that a rigorous research process should specify most of the identified criteria. Applying the content analysis approach, we conducted a systematic literature review of case studies published in the basket-of-eight journals in IS to ascertain researchers’ approach towards stipulated rigor criteria. Our result and observation indicate that although researchers prioritise rigour in the conduct of their research, there is an increasing rate of idiosyncratic research practices in addition to dearth of guidelines for analysing qualitative data in information systems research.

Project management is more efficient and effective when project stakeholders are socially aligned on what the project objectives are and how they should be achieved. This outcome occurs because social alignment reduces the friction amongst stakeholders each time a project management decision is made. Yet, how social alignment develops or dissolves over time in a complex project is unknown. This research develops a dynamic model of social alignment and misalignment, and it identifies some of the project controls that appear to affect their development. Drawing on interview and observational data from 17 respondents involved in a complex health-IT project over a two-year period, we show that social alignment and misalignment involve eight stages – separation, disrespect, lack of cross-discipline participation and social misalignment through to learning, respect, cross-discipline participation and ultimately, social alignment. The research has implications for how researchers theorize social alignment in complex projects and how practitioners can facilitate its development.

Active technological development has fuelled rapid growth in the number of Unmanned Aerial Vehicle (UAV) platforms being deployed around the globe. Improved sensors and enhanced image processing techniques have consolidated and confirmed UAVs as the technology of choice. Many jurisdictions have regulated stringent restrictions on flying UAVs in numerous scenarios where they could be of great value. Whilst no doubt wise and prudent, this abundance of caution constrains the full potential of UAV technology. Despite the increased regulation, UAVs or drones have rapidly become the tool of choice for both the environmental science and the remote sensing communities. This is due, in no small part, to a lowering cost of entry. The last few years has seen significant technological development in UAV platforms, sensor miniaturisation, and robotic sensing. UAV technology progresses apace. The design of novel UAV systems and the use of UAV platforms integrated with RGB, multispectral, hyperspectral, thermal imaging, gas sensing and/or laser scanning sensors have now been demonstrated in both research and practical applications. Novel UAV platforms, UAV-based sensors, robotic sensing and imaging techniques, the development of processing workflows, as well as the capacity of ultra-high temporal and spatial resolution data, provide both opportunities and challenges that will allow engineers and scientists to address novel and important scientific questions in UAV and sensor design, remote sensing and environmental monitoring. This work features papers on UAV sensor design; improvements in UAV sensor technology; obstacle detection, methods for measuring optical flow; target tracking; gimbal influence on the stability of UAV images; augmented reality tools; segmentation in digital surface models for 3D reconstruction; detecting the location and grasping objects; multi-target localization; vision-based tracking in cooperative multi-UAV systems; noise suppression techniques; rectification for oblique images; two-UAV communication system; fuzzy-based hybrid control algorithms; pedestrian detection and tracking as well as a range of atmospheric, geological, agricultural, ecological, reef, wildlife, building and construction; coastal area coverage; search and rescue (SAR); water plume temperature measurements; aeromagnetic and archaeological survey applications.

Active technological development has fuelled rapid growth in the number of Unmanned Aerial Vehicle (UAV) platforms being deployed around the globe. Improved sensors and enhanced image processing techniques have consolidated and confirmed UAVs as the technology of choice. Many jurisdictions have regulated stringent restrictions on flying UAVs in numerous scenarios where they could be of great value. Whilst no doubt wise and prudent, this abundance of caution constrains the full potential of UAV technology. Despite the increased regulation, UAVs or drones have rapidly become the tool of choice for both the environmental science and the remote sensing communities. This is due, in no small part, to a lowering cost of entry. The last few years has seen significant technological development in UAV platforms, sensor miniaturisation, and robotic sensing. UAV technology progresses apace. The design of novel UAV systems and the use of UAV platforms integrated with RGB, multispectral, hyperspectral, thermal imaging, gas sensing and/or laser scanning sensors have now been demonstrated in both research and practical applications. Novel UAV platforms, UAV-based sensors, robotic sensing and imaging techniques, the development of processing workflows, as well as the capacity of ultra-high temporal and spatial resolution data, provide both opportunities and challenges that will allow engineers and scientists to address novel and important scientific questions in UAV and sensor design, remote sensing and environmental monitoring. This work features papers on UAV sensor design; improvements in UAV sensor technology; obstacle detection, methods for measuring optical flow; target tracking; gimbal influence on the stability of UAV images; augmented reality tools; segmentation in digital surface models for 3D reconstruction; detecting the location and grasping objects; multi-target localization; vision-based tracking in cooperative multi-UAV systems; noise suppression techniques; rectification for oblique images; two-UAV communication system; fuzzy-based hybrid control algorithms; pedestrian detection and tracking as well as a range of atmospheric, geological, agricultural, ecological, reef, wildlife, building and construction; coastal area coverage; search and rescue (SAR); water plume temperature measurements; aeromagnetic and archaeological survey applications.

The past decade has borne witness to a remarkable growth in the use of UAVs as remote sensing platforms. A wide range and selection of commercially available UAV platforms have entered the market. They can be acquired off-the-shelf at increasingly lower cost. This availability and affordability has been complemented by rapid advances in the miniaturization of cameras, sensors, instrumentation and data stores and transmission systems. UAV platforms have become smarter, more adroit, and more dexterous. The sensors they fly are lighter, cheaper, more compact, sophisticated and sensitive. Adoption of UAV technology has brought about a revolution in environmental monitoring. This transformative UAV innovation has been enthusiastically embraced by remote sensing applications and scientific disciplines. This book highlights advances in sensor technologies, navigation systems and sensors payloads including the following: autonomous aerial refueling; calibration method using low cost MEM IMUs; low cost airborne sensing systems; vision-based detection; UAVs task and motion planning in the presence of obstacles; ground-based radio navigation systems; smart flying sensors; UAV control using 3D landmark bearing-only observations; cooperative surveillance and pursuit; new multispectral camera system with different bandpass filters; synthetic aperture radar to aid UAV navigation; formation flight of multiple UAVs; shared autonomy; dual-stack single-radio communication architectures; GNSS-based passive radar; UAV navigation in cluttered and GPS-denied environments and UAV-based photogrammetry. The book also highlights a diverse range of new applicators including the estimation of carbon exports from heterogeneous soil landscapes; instruments to classify the water content feature of lands; wildlife monitoring and conservation; wildlife poachers detection; architectural surveys of vertical structures; environmental source localization and tracking; dust particles after blasting at open-pit mine sites; data collection from WSNs; inspection of pole-like structures; multi-UAV routing; emergency response; river hydromorphological features detection; dynamic UAV routing in traffic incident monitoring, and surveys on methods and inexpensive platforms for infrastructure inspection.

When analyzing or designing information systems, users often work with multiple conceptual models because each model articulates a different, partial aspect of a real-world domain. However, the available research in this area has largely studied the use of single modeling artefacts only. We develop new theory about interpreting multiple conceptual models that details propositions for evaluation of individuals’ selection, understanding, and perceived usefulness of multiple conceptual models. We detail several implications of our theory development for empirical research on conceptual modeling. We also outline practical contributions for the design of conceptual models and for choosing models for systems analysis and design tasks. Finally, to stimulate research that builds on our theory, we illustrate procedures for enacting our theory and discuss a range of empirically relevant boundary conditions.

A computationally efficient reduced-order electrochemical-thermal model for small-format cylindrical lithium ion cells is developed, by applying the Pade approximation technique to the Pseudo-2-Dimensional battery model. Whence the amount of the total heat produced in the battery is obtained which in turn allows the evolution of the cell temperature is computed based on a simplified thermal model. The proposed model is computationally efficient whilst its accuracy compares favorably with those obtained using the 1-dimensional radial electrochemical-thermodynamic model implemented in Comsol Multiphysics.

The existence of a relationship between dialogue and engagement is an idea that has been present since the two concepts emerged as discrete entities in the organizational literature in the early 1990s (Johnston, 2014). Such a link is logical given the apparent similarities between the forms and functions of dialogue and engagement (Taylor & Kent, 2014). Engagement and dialogue share an association to the idea of relationships—a focal concept in public relations, marketing, organizational communication and other areas. This chapter advances a model of multi-level interconnectedness between engagement and dialogue, where dialogue provides both an orientation within which engagement can occur; and a specific way in which communication is operationalized within that engagement. This dialogic engagement is generated out of a context that draws on principles of dialogue to create an environment within which organizations and their stakeholders hold positive views of each other and the conduct of shared communication, and therefore wish to engage with each other. A mutually-beneficial outcome is frequently a consequence of the interaction that is generated out of this environment, but a desire for that outcome is not always a characteristic of the environment. The positive views the participants have of each other make them want to engage.

The increasing use of Photovoltaic panels (PVs) in residential areas may likely lead to addition of central electric energy storage (EESs) by retailers for load transfer capabilities. Such arrangement can provide flexibility for grid by shifting stored energy over the time. Likewise, the dispatchability of concentrated solar power (CSP) with thermal energy storage (TES) will have the same impact on the electricity network. This paper proposes method and assessing process to compare and examine the difference between the impacts of the two noted schemes.

Multilevel Modular Cascade Converters (MMCC) can be used to provide higher effective switching frequencies and reduce harmonic distortion in classical converter problems such as BESS and STATCOM. To successfully implement a MMCC in a STATCOM application it is necessary to balance dc-link voltages of the individual modules and track a reference output current. This work presents master and individual module controls utilizing feedback linearization and sliding mode control. Simulation results demonstrate that the control strategy presented in this paper can balance dc-link voltages of individual modules and provide output current tracking within the first cycle.

This paper proposes a control design for enhancing current sharing among distributed reactive power generators by improving cooperation among voltage controllers in a Microgrid system. A novel control approach based on sharing information with immediate neighbours as modified by current droop is proposed to regulate the voltage and to control the reactive current injection sharing in a distribution feeder. In this paper, the control algorithm uses localized information as well as from the nearest neighbors. Modified consensus shows low communication requirements, good convergence, and good sharing of the compensation current among the inverters. To evaluate the performance of the algorithm, photovoltaic (PV) systems are included in the examples. The key contribution of this paper is to use the adjacency update with a form of droop control.

Highlights - CoCr graded femoral stems attain reduced bone-stress shielding, stability, and bone-equivalent stiffness, in silico and in vitro. - Reversed AGS model failed balanced bone-implant micromotions on promoting bone osseointegration. - Dense RGS, hollow RGS, and proximal AGS increased Gruen zone 7 stress values by 3 − 4.7 times that of Ti stems. - Proximal AGS and hollow RGS are highlighted to be adopted for an innovative load-sharing femoral stems. Abstract The incapability of controlling relative micromotions and load transfers to a peri-prosthetic femur shortens implant longevity. This study aims to evaluate the possibility of applying graded porous cobalt chromium (CoCr) to cementless femoral stems. 3D finite element analyses and physical testings of hip implants were conducted with four different grading orientations, along the axial and radial planes of the femoral stem. The results show that the CoCr graded femoral stems with a porosity decreased caudally and inwardly may control the relative micromotions in an acceptable range for bone ingrowth, significantly increase stress transfers on the Gruen zone 1 and 7, and attain the flexural stiffness comparable to human femurs. Therefore, CoCr graded femoral stems demonstrate great potential for applications in implants with reduced stress shielding and improved long-term survival rates.

The influx of solar photovoltaic (PV) systems on distribution networks worldwide has presented many challenges for distribution network service providers (DNSPs) including voltage regulation and voltage imbalance in low voltage networks. In Australia, low voltage networks are typically not well monitored and accurate and reliable software models do not exist. As such, the impact of emerging technologies on low voltage networks are not well understood. This paper implements a distribution system load flow method in Matlab to model a section of Queensland DNSP Energex's low voltage network. The model is validated by comparing load flow results to recorded meter data and its use is then demonstrated by performing a scenario simulation whereby the radial network is meshed. It is observed that meshing of radial branches in the modelled network significantly improves voltage regulation and voltage imbalance.

The dispatchability of concentrated solar power (CSP) with thermal energy storage (TES) offers the ability to provide ancillary services (AS) such as spinning reserve and frequency regulation. In this paper, the energy and ancillary services value of CSP-TES in the Australian national electricity market (NEM) is estimated using production cost simulation (PCS) of the NEM system by the PLEXOS software. This study also compares the energy benefits of a CSP plant with TES estimated from the PCS of the NEM using a generator short run marginal cost (SRMC) based stack model and that obtained from the PCS using a generator bids based stack model. The latter model is more realistic as it uses actual generator bids data in the market and our results show that the energy benefits of a CSP with TES in the NEM estimated from the latter model is significantly higher than that estimated from the former model.

Background The widespread reliance on motor vehicles has negative effects on both the environment and human health. The development of an innovative in-vehicle human-machine interface (HMI) has the potential to contribute to reducing traffic pollution and road trauma. Aim A qualitative study, using a driver-centred design approach, was carried out to test how best to provide ecological and safe (eco-safe) driving advice and feedback to drivers on their driving style via an in-vehicle HMI. Method A total of 34 drivers (52.9% males), aged 19-61 years, participated in focus groups which explored concepts from the Technology Acceptance Model (Davis, 1989) Findings Main themes emerging from the focus groups were: (i) perceived importance of eco-safe driving behaviour; (ii) perceived usefulness of eco-safe in-vehicle HMIs; (iii) intentions to use an eco-safe in-vehicle HMI; (iv) perceptions towards eco-safe in-vehicle HMI design characteristics; and (v) potential problems associated with using eco-safe in-vehicle HMIs. Implications This study provides the foundation to inform the design and development of an evidence-based in-vehicle eco-safe HMI with high levels of driver acceptance. Recommendations for future research are also discussed.

"Understanding People-Environment relationships is a key aspect of future improvement in landscape architectural research. Designers need to explore user’s experience in order to make sensible design decisions. This paper reports on an environmental gerontology research project which has sought to understand aged care residents’ user experiences of their outdoor landscape designed environment. Using Digital Storytelling and Go-Along methods as techniques to engage users, this research was able to draw out the residents lived experiences of the gardens provided within their aged care facilities. This approach was adopted to empower users, especially senior users, to voice their opinions. Fieldwork was conducted over two years across two different aged care facilities in Queensland, Australia. The purpose of this research is twofold: to develop a more comprehensive understanding of individual user experiences by investigating the factors that contribute to user engagement in their outdoor environment; and to explore the role of participatory media in understanding user experience within a landscape design context. The findings of this research show that these outdoor landscapes contribute not only to a therapeutic experience, but can also actively construct a ‘healthful landscape’. User’s landscape experiences are deeply connected with personal memories. Individual landscape memories influence user’s experiences in positive ways. Plant gifting/exchange is a common and important practice of social interaction among residents. It positively contributes to a healthful landscape experience by connecting to personal memories, as well as to each other. The richness of garden colors and form also plays a more important role in making these spaces a vibrant experience for aging users. Finally, ease of maintenance was shown to be an important enabler for residents’ active engagement in their landscapes. These findings could assist in implementing strategies to inform and enable future design solutions in an ageing society."

The use of porous cellular structures in bone tissue engineering can provide mechanical and biological environments closer to the host bone. However, poor internal architectural designs may lead to catastrophic failure. In this work, 192 open-porous cellular structures were fabricated using 3D printing (3DP) techniques. The mechanical and biological behavior of four 3D internal structures (octahedral, pillar octahedral, cubic and truncated octahedral) was investigated. It was found that the pillar octahedral shape has not only greater stiffness and strength under compression, shear and torsion but increased rate of pre-osteoblastic cell proliferation. We believe bone implants can be fabricated using 3DP techniques and their mechanical and biological performance can be tailored by modifying the internal architectures.

Authentication and authenticated encryption with associated data (AEAD) are applied in cryptographic protocols to provide message integrity. The definitions in the literature and the constructions used in practice all protect against forgeries, but offer varying levels of protection against replays, reordering, and drops. As a result of the lack of a systematic hierarchy of authentication and AEAD security notions, gaps have arisen in the literature, specifically in the provable security analysis of the Transport Layer Security (TLS) protocol. We present a hierarchy of authentication and AEAD security notions, interpolating between the lowest level of protection (against forgeries) and the highest level (against forgeries, replays, reordering, and drops). We show generically how to construct higher level schemes from a basic scheme and appropriate use of sequence numbers, and apply that to close the gap in the analysis of TLS record layer encryption. This is a post-peer-review, pre-copyedit version of an article published in [Cryptographers’ Track at the RSA Conference]. The final authenticated version is available online at: https://link.springer.com/chapter/10.1007%2F978-3-319-29485-8_4#enumeration

This paper describes a concept for a collision avoidance system for ships, which is based on model predictive control. A finite set of alternative control behaviors are generated by varying two parameters: offsets to the guidance course angle commanded to the autopilot and changes to the propulsion command ranging from nominal speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, compliance with the Convention on the International Regulations for Preventing Collisions at Sea and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon, and the optimal control behavior is selected. Robustness to sensing error, predicted obstacle behavior, and environmental conditions can be ensured by evaluating multiple scenarios for each control behavior. The method is conceptually and computationally simple and yet quite versatile as it can account for the dynamics of the ship, the dynamics of the steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions. This is the authors' accepted and refereed manuscript to the article. © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

There has been a long-running discourse in the information systems literature around the business value of IT (BVIT). Researchers have adopted a myriad of conceptual, theoretical and analytical approaches to evaluating the tangible and intangible measures of BVIT. Little research however, has explored richer theoretical explanations of the dynamic nature of the BVIT processes in contemporary dynamic business environments. To address this gap, this research in progress seeks to explore how BVIT is created as a bottom-up emergent process. In pursuit of such understanding, this research embraces complex adaptive systems (CAS) theory to develop a bottom-up conceptual model of BVIT. The agent-based modelling (ABM) technique is introduced as an analytical tool for computationally representing and examining the CAS model of BVIT. Operationalization of the CAS model and ABM modelling will be demonstrated through a theory building exercise.

Highly efficient loading of bone morphogenetic protein-2 (BMP-2) onto carriers with desirable performance is still a major challenge in the field of bone regeneration. Till now, the nanoscaled surface-induced changes of the structure and bioactivity of BMP-2 remains poorly understood. Here, the effect of nanoscaled surface on the adsorption and bioactivity of BMP-2 was investigated with a series of hydroxyapatite surfaces (HAPs): HAP crystal-coated surface (HAP), HAP crystal-coated polished surface (HAP-Pol), and sintered HAP crystal-coated surface (HAP-Sin). The adsorption dynamics of recombinant human BMP-2 (rhBMP-2) and the accessibility of the binding epitopes of adsorbed rhBMP-2 for BMP receptors (BMPRs) were examined by a quartz crystal microbalance with dissipation. Moreover, the bioactivity of adsorbed rhBMP-2 and the BMP-induced Smad signaling were investigated with C2C12 model cells. A noticeably high mass-uptake of rhBMP-2 and enhanced recognition of BMPR-IA to adsorbed rhBMP-2 were found on the HAP-Pol surface. For the rhBMP-2-adsorbed HAPs, both ALP activity and Smad signaling increased in the order of HAP-SinHAPHAP-Pol. Furthermore, hybrid molecular dynamics and steered molecular dynamics simulations validated that BMP-2 tightly anchored on the HAP-Pol surface with a relative loosened conformation, but the HAP-Sin surface induced a compact conformation of BMP-2. In conclusion, the nanostructured HAPs can modulate the way of adsorption of rhBMP-2, and thus the recognition of BMPR-IA and the bioactivity of rhBMP-2. These findings can provide insightful suggestions for the future design and fabrication of rhBMP-2-based scaffolds/implants.This study provides strong evidences that nanoscaled HAPs yield extraordinary influence on the adsorption behaviors and bioactivity of rhBMP-2. It has been found that the surface roughness and crystallinity played a crucial role in governing the way of rhBMP-2 binding to HAPs, and thus the conformation, recognition of BMPR-IA and bioactivity of adsorbed rhBMP-2. It is also for the first time to correlate numerical modeling and experimental results of the bioactivity of rhBMP-2 on nanostructured HAPs. This work can pave an avenue for the wider uses of rhBMP-2 in clinical applications and arouse broad interests among researchers in the fields of nano-biotechnology, biomaterials and bone tissue engineering.

Upon infection, Legionella pneumophila uses the Dot/Icm type IV secretion system to translocate effector proteins from the Legionella-containing vacuole (LCV) into the host cell cytoplasm. The effectors target a wide array of host cellular processes that aid LCV biogenesis, including the manipulation of membrane trafficking. In this study, we used a hidden Markov model screen to identify two novel, non-eukaryotic soluble NSF attachment protein receptor (SNARE) homologs: the bacterial Legionella SNARE effector A (LseA) and viral SNARE homolog A proteins. We characterized LseA as a Dot/Icm effector of L. pneumophila, which has close homology to the Qc-SNARE subfamily. The lseA gene was present in multiple sequenced L. pneumophila strains including Corby and was well distributed among L. pneumophila clinical and environmental isolates. Employing a variety of biochemical, cell biological and microbiological techniques, we found that farnesylated LseA localized to membranes associated with the Golgi complex in mammalian cells and LseA interacted with a subset of Qa-, Qb- and R-SNAREs in host cells. Our results suggested that LseA acts as a SNARE protein and has the potential to regulate or mediate membrane fusion events in Golgi-associated pathways.

Acoustic classification of anurans (frogs) has received increasing attention for its promising application in biological and environment studies. In this study, a novel feature extraction method for frog call classification is presented based on the analysis of spectrograms. The frog calls are first automatically segmented into syllables. Then, spectral peak tracks are extracted to separate desired signal (frog calls) from background noise. The spectral peak tracks are used to extract various syllable features, including: syllable duration, dominant frequency, oscillation rate, frequency modulation, and energy modulation. Finally, a k-nearest neighbor classifier is used for classifying frog calls based on the results of principal component analysis. The experiment results show that syllable features can achieve an average classification accuracy of 90.5% which outperforms Mel-frequency cepstral coefficients features (79.0%).

The regulatory framework for corporate governance, both in Australia and internationally, shifts between rules based regimes and principles based approach. The rules based regimes are typified by legislation that imposes mandated compliance based rules, such as the Sarbanes Oxley Act. Other regimes, such as Australia’s CLERP 9 and the ASX Corporate Governance Council’s principles, have opted for a disclosure approach. This paper examines these approaches in the context of the non-binding vote rule, which arguably combines aspects of both. The study’s methodology empirically considers evidence relating to actual voting patterns as well as case study examples of the non-binding vote’s effectiveness. Significantly, our analyses show that from its inception, the non-binding vote was effective in motivating management to change the remuneration package to one they perceived as more acceptable to shareholders and that the non-binding vote is an effective regime to manage CEO remuneration (and by extension) executive remuneration.

This paper presents a system to analyze long field recordings with low signal-to-noise ratio (SNR) for bio-acoustic monitoring. A method based on spectral peak track, Shannon entropy, harmonic structure and oscillation structure is proposed to automatically detect anuran (frog) calling activity. Gaussian mixture model (GMM) is introduced for modelling those features. Four anuran species widespread in Queensland, Australia, are selected to evaluate the proposed system. A visualization method based on extracted indices is employed for detection of anuran calling activity which achieves high accuracy.

This paper analyses the compulsory modulation of the amounts of fines imposed respectively on private individuals and legal entities for the same acts, as established in art. 31 ter 1 of the Penal Code (after the reorganisation resulting from the reform of 2015). This obligation becomes particularly significant given the pre-eminence of the fine as the only penalty of mandatory imposition for legal entities. It also calls into question the supposed independence of the criminal liability of the legal entity compared to that imposed on the private individual. Without forgetting that it poses numerous interpretive problems subject to intense doctrinal discussions, which are presented in this paper, adopting a reasoned approach to the matter.

This chapter focuses on the political impact of two key elements that were introduced in the revised 2005 International Health Regulations (IHR) that directly engage the role of the individual as much as the state and the World Health Organization (WHO): recognition of human rights principles in outbreak response, and the allowance for non-state actors to directly communicate with WHO and share outbreak surveillance intelligence.

This article canvasses recent case law adjudicating the uneasy disclosure balance between the interests of the insurer and the insured in the process of transacting an insurance contract. It examines also the consequences of non-disclosure and misrepresentation and whether the avowed legislative intent — that the liability of the insurer in respect of a claim is to be reduced to the amount that would place the insurer in the position it would have been had the non-disclosure or misrepresentation not occurred — is being achieved in practice. As there is no doubt as to who bears the onus of proof as to non-disclosure or misrepresentation it is surprising that insurers continue to flounder in this regard in relation to underwriting guidelines and adherence to them. The article reviews recent case law in this context and stresses that an insurer wishing to preserve its capacity to avoid liability on the basis that it would not have entered into a contract at all had the true situation been known to it must maintain detailed underwriting guidelines supported by consistent adherence to those guidelines. Recent case law also emphasises that the insurer must provide clear and cogent admissible evidence from appropriate personnel and officers of the company to discharge its onus.

In order for cells to stop moving, they must synchronously stabilize actin filaments and their associated focal adhesions. How these two structures are coordinated in time and space is not known. We show here that the actin association protein Tm5NM1, which induces stable actin filaments, concurrently suppresses the trafficking of focal-adhesion-regulatory molecules. Using combinations of fluorescent biosensors and fluorescence recovery after photobleaching (FRAP), we demonstrate that Tm5NM1 reduces the level of delivery of Src kinase to focal adhesions, resulting in reduced phosphorylation of adhesion-resident Src substrates. Live imaging of Rab11-positive recycling endosomes that carry Src to focal adhesions reveals disruption of this pathway. We propose that tropomyosin synchronizes adhesion dynamics with the cytoskeleton by regulating actin-dependent trafficking of essential focal-adhesion molecules. NHMRC Grant 512251 and ARC Discovery Projects DP130100269 and DP1095468

Research question / issue This paper frames the debate on corporate governance convergence in terms of the morality underlying corporate governance models. The claims and arguments of moral relativism are presented to provide theoretical structure to the moral aspects of corporate governance convergence, and ultimately the normative question of whether convergence should occur. Research findings / insights: The morality underlying different models of corporate governance has largely been ignored in the corporate governance convergence literature. A range of moral philosophies and principles that underlie the dominant corporate governance models are identified. This leads to a consideration of the claims and arguments of moral relativism relating to corporate governance. A research agenda around the claims of Descriptive and Metaethical moral relativism, and which ultimately informs the associated normative argument, is then suggested. Theoretical / Academic implications The application of moral relativism to the debate on corporate governance convergence presents a theoretical structure to the analysis and consideration of its moral aspects. This structure lends itself to further research, both empirical and conceptual. Practitioner / Policy implications The claims and arguments of moral relativism provide a means of analysing calls that are made for a culturally or nationally ‘appropriate’ model of corporate governance. This can assist in providing direction for corporate governance reforms and is of particular relevance for developing countries which have inherited Western corporate governance models through colonialism.

The requirement of the trace element selenium for life and its beneficial role in human health has been known for several decades. This is attributed to low molecular weight selenium compounds, as well as to its presence within at least 25 proteins, named selenoproteins, in the form of the amino acid selenocysteine (Sec). Incorporation of Sec into selenoproteins employs a unique mechanism that involves decoding of the UGA codon. This process requires multiple features such as the selenocysteine insertion sequence (SECIS) element and several protein factors including a specific elongation factor EFSec and the SECIS binding protein 2, SBP2. The function of most selenoproteins is currently unknown; however, thioredoxin reductases (TrxR), glutathione peroxidases (GPx) and thyroid hormone deiodinases (DIO) are well characterised selenoproteins involved in redox regulation of intracellular signalling, redox homeostasis and thyroid hormone metabolism. Recent evidence points to a role for selenium compounds as well as selenoproteins in the prevention of some forms of cancer. A number of clinical trials are either underway or being planned to examine the effects of selenium on cancer incidence. In this review we describe some of the recent progress in our understanding of the mechanism of selenoprotein synthesis, the role of selenoproteins in human health and disease and the therapeutic potential of some of these proteins.

Many building sustainable rating tools rate the effectiveness of a building’s contribution to a better world environment by measuring its performance in relation mostly to energy with additional emphasis in other aspects such as water, waste, indoor environment quality, transport, materials, and emissions. A simplified analysis is tabled to highlight the limited direct response of most green building rating tools to the health and well-being of building occupants. Inquiry into this deficit identifies a few salient points as a preamble to a larger discussion of use of rating tools to assess effectiveness of sustainability and the impact on ecology. Past notions of a sustainable planet resided in the making of sustainable buildings that reduced consumption of energy and other resources. The increased interest in creating healthier office environments as a sustainable action needs further analysis especially in relation to the ecological environment.

This chapter explores the status of the current programs designed to address global tax avoidance, critiques the role that the G20 plays in the reform agenda, and considers the part that Australia will play in the process.