An efficient and robust system for multi-person event detection in real world indoor surveillance scenes

Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

The second chance project: A multi-level examination of secondary prevention practices for Saudi people following a recent cardiac event

The study examined the health-related behaviours of Saudi people following a recent cardiac event and identified the factors that influence these behaviours using McLeroy et al.'s (1988) Ecological Model of Health Behaviours as a guiding framework. The study was one of the first in Saudi Arabia to examine the health-related behaviours of Saudi people following a recent cardiac event. The study findings emphasise the importance of a program that integrates secondary prevention practices, educational approaches and targeted supportive services in cardiac care in Saudi Arabia.

Multi-faceted visualisation of worklists

Due to the popularity of modern Collaborative Virtual Environments, there has been a related increase in their size and complexity. Developers therefore need visualisations that expose usage patterns from logged data, to understand the structures and dynamics of these complex environments. This chapter presents a new framework for the process of visualising virtual environment usage data. Major components, such as an event model, designer task model and data acquisition infrastructure are described. Interface and implementation factors are also developed, along with example visualisation techniques that make use of the new task and event model. A case study is performed to illustrate a typical scenario for the framework, and its benefits to the environment development team.

Sportway toward sport event consumption

Research has lead to a proliferation of multi-attribute scales to understand the motives for sport event attendance. The large number of potential motives, coupled with the long questionnaires needed to measure them, creates challenges for sport marketing research in natural populations. This research brings parsimony to the study of sport consumer behaviour by developing and testing a core set of five SportWay facets of motivation. Results provide guidance to sport marketing professionals and academics in survey development decisions related to selecting the most appropriate motives and items.

An event-based traffic flow model for traffic control at railway junctions

This paper introduces an event-based traffic model for railway systems adopting fixed-block signalling schemes. In this model, the events of trains' arrival at and departure from signalling blocks constitute the states of the traffic flow. A state transition is equivalent to the progress of the trains by one signalling block and it is realised by referring to past and present states, as well as a number of pre-calculated look-up tables of run-times in the signalling block under various signalling conditions. Simulation results are compared with those from a time-based multi-train simulator to study the improvement of processing time and accuracy.

Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions

In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.

Multi-method, multi-theoretical, multi-level research in the learning sciences

We examine methodologies and methods that apply to multi-level research in the learning sciences. In so doing we describe how multiple theoretical frameworks informs the use of different methods that apply to social levels involving space-time relationships that are not accessible consciously as social life is enacted. Most of the methods involve analyses of video and audio files. Within a framework of interpretive research we present a methodology of event-oriented social science, which employs video ethnography, narrative, conversation analysis, prosody analysis, and facial expression analysis. We illustrate multi-method research in an examination of the role of emotions in teaching and learning. Conversation and prosody analyses augment facial expression analysis and ethnography. We conclude with an exploration of ways in which multi-level studies can be complemented with neural level analyses.

SAIVT-QUT@TRECVid 2012 : interactive surveillance event detection

In this paper, we propose an approach which attempts to solve the problem of surveillance event detection, assuming that we know the definition of the events. To facilitate the discussion, we first define two concepts. The event of interest refers to the event that the user requests the system to detect; and the background activities are any other events in the video corpus. This is an unsolved problem due to many factors as listed below: 1) Occlusions and clustering: The surveillance scenes which are of significant interest at locations such as airports, railway stations, shopping centers are often crowded, where occlusions and clustering of people are frequently encountered. This significantly affects the feature extraction step, and for instance, trajectories generated by object tracking algorithms are usually not robust under such a situation. 2) The requirement for real time detection: The system should process the video fast enough in both of the feature extraction and the detection step to facilitate real time operation. 3) Massive size of the training data set: Suppose there is an event that lasts for 1 minute in a video with a frame rate of 25fps, the number of frames for this events is 60X25 = 1500. If we want to have a training data set with many positive instances of the event, the video is likely to be very large in size (i.e. hundreds of thousands of frames or more). How to handle such a large data set is a problem frequently encountered in this application. 4) Difficulty in separating the event of interest from background activities: The events of interest often co-exist with a set of background activities. Temporal groundtruth typically very ambiguous, as it does not distinguish the event of interest from a wide range of co-existing background activities. However, it is not practical to annotate the locations of the events in large amounts of video data. This problem becomes more serious in the detection of multi-agent interactions, since the location of these events can often not be constrained to within a bounding box. 5) Challenges in determining the temporal boundaries of the events: An event can occur at any arbitrary time with an arbitrary duration. The temporal segmentation of events is difficult and ambiguous, and also affected by other factors such as occlusions.

Property case competition : multi-stakeholder reflection

Pacific Rim Real Estate Society has conducted four property case competitions from 2009 to 2012. The competition provides opportunities for undergraduate students to present their proposal on a given case study. All students were locked down with their four team members for five hours without external help to ensure a level playing field across participants. Students prepared their presentation and defended their arguments in front of experts in property industry and academia. The aim of this paper is reflecting on the feedback received from stakeholders involved in the case competition. Besides exploring what students have gained from the competitions, this paper provides an insight on the opportunities and challenges for the new format of competition to be introduced in 2013. Over the last four competitions, there were three universities participated in all the four consecutive events, four universities partook in two events and another four universities only competed once. Some universities had a great advantage by having previous experiences by participating in similar international business competitions. Findings show that the students have benefited greatly from the event including improving their ability in problem solving and other non-technical skills. Despite the aforementioned benefits, the PRRES closed-book case competition is proven not viable thus future competition needs to minimise the travel and logistic cost.

The ZomPoc Project. A Large Scale Public ARG Event

An experiment in large scale, live, game design and public performance, bringing together participants from across the creative arts to design, deliver and document a project that was both a cooperative learning experience and an experimental public performance. The four month project, funded by the Edge Digital Centre, culminated into a 24 hour ARG event involving over 100 participants in December 2012. Using the premise of a viral outbreak, young enthusiasts auditioned for the roles of Survivor, Zombie, Medic and Military. The main objective was for the Survivors to complete a series of challenges over 24 hours, while the other characters fulfilled their opposing objectives of interference and sabotage supported by both scripted and free-form scenarios staged in constructed scenes throughout the venues. The event was set in the State Library of Queensland and the Edge Digital Centre who granted the project full access, night and day to all areas including public, office and underground areas. These venues were transformed into cinematic settings full of interactive props and various audio-visual effects. The ZomPoc Project was an innovative experiment in writing and directing a large scale, live, public performance, bringing together participants from across the creative industries. In order to design such an event a number of innovative resources were developed exploiting techniques of game design, theatre, film, television and tangible media production. A series of workshops invited local artists, scientists, technicians and engineers to find new ways of collaborating to create networked artifacts, experimental digital works, robotic props, modular set designs, sound effects and unique costuming guided by an innovative multi-platform script developed by Deb Polson. The result of this collaboration was the creation of innovative game and set props, both atmospheric and interactive. Such works animated the space, presented story clues and facilitated interactions between strangers who found themselves sharing a unique experience in unexpected places.

Stored blood products augment inflammation in a two-event model of Transfusion Related Acute Lung Injury (TRALI)

Aim/Background TRALI is hypothesised to develop via a two-event mechanism involving both the patieint's underlying morbidity and blood product factors. The storage of cellular products has been implicated in cases of non-antibody mediated TRALI, however the pathophysiological mechanisms are undefined. We investigated blood product storage-related modulation of inflmmatory cells and medicators involved in TRALI. Methods In an in vitro mode, fresh human whole blood was mixed with culture media (control) or LPS as a 1st event and "transfused" with 10% (v/v) pooled supernatant (SN) from Day 1 (d1, n=75) or Day 42 (D42, n=113) packed red blood cells (PRBCs) as a 2nd event. Following 6hrs, culture SN was used to assess the overall inflammatory response (cytometric bead array) and a duplicate assay containing protein transport inhibitor was used to assess neutrophil- and monocyte-specific inflmamatory responses using multi-colour flow cytometry. Panels: IL-6, IL-8, IL-10, IL-12, IL-1, TNF, MCP-1, IP-10, MIP-1. One-way ANOVA 95% CI. Results In the absence of LPS, exposure to D1 or D42 PRBC-SN reduced monocyte expression of IL-6, IL-8 and Il-10. D42 PRBC-SN also reduced monocyte IP-10, and the overall IL-8 production was increased. In the presence of LPS, D1-PRBC SN only modified overall IP-10 levels which were reduced. However, cf LPS alone, the combination of LPS and D42 PRBC-SN resulted in increased neutrophil and monocyte productionof IL-1 and IL-8 as well as reduced monocyte TNF production. Additionally, LPS and D42 PRBC-SN resulted in overall inflmmatory changes: elevated IL-8,

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

Audio signalling as a backup communication channel for multi-robot systems

This paper presents a low-bandwidth multi-robot communication system designed to serve as a backup communication channel in the event a robot suffers a network device fault. While much research has been performed in the area of distributing network communication across multiple robots within a system, individual robots are still susceptible to hardware failure. In the past, such robots would simply be removed from service, and their tasks re-allocated to other members. However, there are times when a faulty robot might be crucial to a mission, or be able to contribute in a less communication intensive area. By allowing robots to encode and decode messages into unique sequences of DTMF symbols, called words, our system is able to facilitate continued low-bandwidth communication between robots without access to network communication. Our results have shown that the system is capable of permitting robots to negotiate task initiation and termination, and is flexible enough to permit a pair of robots to perform a simple turn taking task.

Experiences with an Object-Oriented, Multi-Stage Language

Metaphor is a multi-stage programming language extension to an imperative, object-oriented language in the style of C# or Java. This paper discusses some issues we faced when applying multi-stage language design concepts to an imperative base language and run-time environment. The issues range from dealing with pervasive references and open code to garbage collection and implementing cross-stage persistence.