Modeling electricity price events as point processes

Energy prices are highly volatile and often feature unexpected spikes. It is the aim of this paper to examine whether the occurrence of these extreme price events displays any regularities that can be captured using an econometric model. Here we treat these price events as point processes and apply Hawkes and Poisson autoregressive models to model the dynamics in the intensity of this process.We use load and meteorological information to model the time variation in the intensity of the process. The models are applied to data from the Australian wholesale electricity market, and a forecasting exercise illustrates both the usefulness of these models and their limitations when attempting to forecast the occurrence of extreme price events.

Detecting anomalous events at railway level crossings

Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

Selecting rainfall events for effective Water Sensitive Urban Design (WSUD) implementation

The current approach for protecting the receiving water environment from urban stormwater pollution is the adoption of structural measures commonly referred to as Water Sensitive Urban Design (WSUD). The treatment efficiency of WSUD measures closely depends on the design of the specific treatment units. As stormwater quality can be influenced by rainfall characteristics, the selection of appropriate rainfall events for treatment design is essential to ensure the effectiveness of WSUD systems. Based on extensive field investigation of four urban residential catchments and computer modelling, this paper details a technically robust approach for the selection of rainfall events for stormwater treatment design using a three-component model. The modelling outcomes indicate that selecting smaller average recurrence interval (ARI) events with high intensity-short duration as the threshold for the treatment system design is the most feasible since these events cumulatively generate a major portion of the annual pollutant load compared to the other types of rainfall events, despite producing a relatively smaller runoff volume. This implies that designs based on small and more frequent rainfall events rather than larger rainfall events would be appropriate in the context of efficiency in treatment performance, cost-effectiveness and possible savings in land area needed.

A novel representation of bioacoustic events for content-based search in field audio data

Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.

InterLACE : a new international collaboration for a Life course approach to women's reproductive health and chronic disease events.

Evidence from population-based studies of women increasingly points to the inter-related nature of reproductive health, lifestyle, and chronic disease risk. This paper describes the recently established International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease. InterLACE aims to advance the evidence base for women's health policy beyond associations from disparate studies by means of systematic and culturally sensitive synthesis of longitudinal data. Currently InterLACE draws on individual level data for reproductive health and chronic disease among 200,000 women from over thirteen studies of women's health in seven countries. The rationale for this multi-study research programme is set out in terms of a life course perspective to reproductive health. The research programme will build a comprehensive picture of reproductive health through life in relation to chronic disease risk. Although combining multiple international studies poses methodological challenges, InterLACE represents an invaluable opportunity to strength evidence to guide the development of timely and tailored preventive health strategies.

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

Honesty about adverse events - more honoured in the breach than in the observance

The medical board of Australia Code of conduct reminds doctors that" "When adverse events occur, you have a responsibility to be open and honest in your communication with your patient, to review what has occurred and to report appropriately." More honoured in the breach rather than the observence may or may not be correct. Faced with the English concerns and the Netherlands research, an evidence based assessment of compliance with the ethical duty to disclose adverse events is warranted.

Managing health risks of extreme weather events : need for a systematic approach

The Climate Commission recently outlined the trend of major extreme weather events in different regions of Australia, including heatwaves, floods, droughts, bushfires, cyclones and storms. These events already impose an enormous health and financial burden onto society and are projected to occur more frequently and intensely. Unless we act now, further financial losses and increasing health burdens seem inevitable. We seek to highlight the major areas for interdisciplinary investigation, identify barriers and formulate response strategies.

Affective events theory as a framework for understanding third-party consumer complaints

Poor complaint management may result in organizations losing customers and revenue. Consumers exhibit negative emotional responses when dissatisfied and this may lead to a complaint to a third-party organization. Since little information is available on the role of emotion in the consumer complaint process or how to manage complaints effectively, we offer an emotions perspective by applying Affective Events Theory (AET) to complaint behavior. This study presents the first application of AET in a consumption context and advances a theoretical framework supported by qualitative research for emotional responses to complaints. In contrast to commonly held views on gender and emotion, men as well as women use emotion-focused coping to complain.

Vulnerability and damage analysis of reinforced concrete framed buildings subjected to near field blast events

Terrorists usually target high occupancy iconic and public buildings using vehicle borne incendiary devices in order to claim a maximum number of lives and cause extensive damage to public property. While initial casualties are due to direct shock by the explosion, collapse of structural elements may extensively increase the total figure. Most of these buildings have been or are built without consideration of their vulnerability to such events. Therefore, the vulnerability and residual capacity assessment of buildings to deliberately exploded bombs is important to provide mitigation strategies to protect the buildings' occupants and the property. Explosive loads and their effects on a building have therefore attracted significant attention in the recent past. Comprehensive and economical design strategies must be developed for future construction. This research investigates the response and damage of reinforced concrete (RC) framed buildings together with their load bearing key structural components to a near field blast event. Finite element method (FEM) based analysis was used to investigate the structural framing system and components for global stability, followed by a rigorous analysis of key structural components for damage evaluation using the codes SAP2000 and LS DYNA respectively. The research involved four important areas in structural engineering. They are blast load determination, numerical modelling with FEM techniques, material performance under high strain rate and non-linear dynamic structural analysis. The response and damage of a RC framed building for different blast load scenarios were investigated. The blast influence region for a two dimensional RC frame was investigated for different load conditions and identified the critical region for each loading case. Two types of design methods are recommended for RC columns to provide superior residual capacities. They are RC columns detailing with multi-layer steel reinforcement cages and a composite columns including a central structural steel core. These are to provide post blast gravity load resisting capacity compared to typical RC column against a catastrophic collapse. Overall, this research broadens the current knowledge of blast and residual capacity analysis of RC framed structures and recommends methods to evaluate and mitigate blast impact on key elements of multi-storey buildings.

Web based surveillance systems could improve disease detection and the response to emerging disease events

The Chinese government should be commended for its open, concerted, and rapid response to the recent H7N9 influenza outbreak. However, the first known case was not reported until 48 days after disease onset.1 Although the difficulties in detecting the virus and the lack of suitable diagnostic methods have been the focus of discussion,2 systematic limitations that may have contributed to this delay have hardly been discussed. The detection speed of surveillance systems is limited by the highly structured nature of information flow and hierarchical organisation of these systems. Flu surveillance usually relies on notification to a central authority of laboratory confirmed cases or presentations to sentinel practices for flu-like illness. Each step in this pathway presents a bottleneck at which information and time can be lost; this limitation must be dealt with...

A discussion of “Estimating the historical and future probabilities of large terrorist events'' by Aaron Clauset and Ryan Woodard

The terrorist attacks in the United States on September 11, 2001 appeared to be a harbinger of increased terrorism and violence in the 21st century, bringing terrorism and political violence to the forefront of public discussion. Questions about these events abound, and “Estimating the Historical and Future Probabilities of Large Scale Terrorist Event” [Clauset and Woodard (2013)] asks specifically, “how rare are large scale terrorist events?” and, in general, encourages discussion on the role of quantitative methods in terrorism research and policy and decision-making. Answering the primary question raises two challenges. The first is identify- ing terrorist events. The second is finding a simple yet robust model for rare events that has good explanatory and predictive capabilities. The challenges of identifying terrorist events is acknowledged and addressed by reviewing and using data from two well-known and reputable sources: the Memorial Institute for the Prevention of Terrorism-RAND database (MIPT-RAND) [Memorial Institute for the Prevention of Terrorism] and the Global Terror- ism Database (GTD) [National Consortium for the Study of Terrorism and Responses to Terrorism (START) (2012), LaFree and Dugan (2007)]. Clauset and Woodard (2013) provide a detailed discussion of the limitations of the data and the models used, in the context of the larger issues surrounding terrorism and policy.

Identifying the Events That Connect Social Media Users : Charting Follower Accession on Twitter

Twitter is the focus of much research attention, both in traditional academic circles and in commercial market and media research, as analytics give increasing insight into the performance of the platform in areas as diverse as political communication, crisis management, television audiencing and other industries. While methods for tracking Twitter keywords and hashtags have developed apace and are well documented, the make-up of the Twitter user base and its evolution over time have been less understood to date. Recent research efforts have taken advantage of functionality provided by Twitter's Application Programming Interface to develop methodologies to extract information that allows us to understand the growth of Twitter, its geographic spread and the processes by which particular Twitter users have attracted followers. From politicians to sporting teams, and from YouTube personalities to reality television stars, this technique enables us to gain an understanding of what prompts users to follow others on Twitter. This article outlines how we came upon this approach, describes the method we adopted to produce accession graphs and discusses their use in Twitter research. It also addresses the wider ethical implications of social network analytics, particularly in the context of a detailed study of the Twitter user base.

Homologs of FT, CEN and FD respond to developmental and environmental signals affecting growth and flowering in the perennial vine kiwifruit

FLOWERING LOCUS T (FT) and CENTRORADIALIS (CEN) homologs have been implicated in regulation of growth, determinacy and flowering. The roles of kiwifruit FT and CEN were explored using a combination of expression analysis, protein interactions, response to temperature in high-chill and low-chill kiwifruit cultivars and ectopic expression in Arabidopsis and Actinidia. The expression and activity of FT was opposite from that of CEN and incorporated an interaction with a FLOWERING LOCUS D (FD)-like bZIP transcription factor. Accumulation of FT transcript was associated with plant maturity and particular stages of leaf, flower and fruit development, but could be detected irrespective of the flowering process and failed to induce precocious flowering in transgenic kiwifruit. Instead, transgenic plants demonstrated reduced growth and survival rate. Accumulation of FT transcript was detected in dormant buds and stem in response to winter chilling. In contrast, FD in buds was reduced by exposure to cold. CEN transcript accumulated in developing latent buds, but declined before the onset of dormancy and delayed flowering when ectopically expressed in kiwifruit. Our results suggest roles for FT, CEN and FD in integration of developmental and environmental cues that affect dormancy, budbreak and flowering in kiwifruit.

Identification and characterization of flowering genes in kiwifruit : sequence conservation and role in kiwifruit flower development

Background Flower development in kiwifruit (Actinidia spp.) is initiated in the first growing season, when undifferentiated primordia are established in latent shoot buds. These primordia can differentiate into flowers in the second growing season, after the winter dormancy period and upon accumulation of adequate winter chilling. Kiwifruit is an important horticultural crop, yet little is known about the molecular regulation of flower development. Results To study kiwifruit flower development, nine MADS-box genes were identified and functionally characterized. Protein sequence alignment, phenotypes obtained upon overexpression in Arabidopsis and expression patterns suggest that the identified genes are required for floral meristem and floral organ specification. Their role during budbreak and flower development was studied. A spontaneous kiwifruit mutant was utilized to correlate the extended expression domains of these flowering genes with abnormal floral development. Conclusions This study provides a description of flower development in kiwifruit at the molecular level. It has identified markers for flower development, and candidates for manipulation of kiwifruit growth, phase change and time of flowering. The expression in normal and aberrant flowers provided a model for kiwifruit flower development.