Observations of the ecological impacts of Sambar Cervus unicolor in East Gippsland, Victoria, with reference to destruction of rainforest communities

Damage caused by Sambar, particularly browsing, antler rubbing and physical removal of particular plant species, is resulting in serious ecological consequences. Threatening processes instigated or maintained by Sambar include: loss of individual taxa, altered vegetation structure and massive
widespread removal and prevention of regeneration, which is now resulting in the loss of plant communities in some areas. These observations are particularly disturbing, as it is apparent that Sambar are yet to reach their full ecological and population potential in south-eastern Australia. The destruction documented ill this article is now so widespread and so severe that in places it represents an ecological disaster for specific plant and animal species, ecological vegetation classes and floristic communities. We strongly recommend that Sambar in particular, and feral deer in general. should no longer be protected under the Wildlife Act 1975 so that control methods can be devised and implemented. It now appears that such measures will he essential for the long-term survival of some fragile plant species and communities in Victoria. (Title: Victorian Naturalist 122(4) 2005, 189-200

Proceedings : 10th International Multimedia Modeling Conference : MMM 2004 : Brisbane, Australia, 5-7 January 2004

The International Multimedia Modelling conference series is an annual forum to discuss the efficient representation, processing, interaction, integration, communication, and retrieval of multimedia information.
In particular, the 10th International Multimedia Modelling Conference (MMM2004) concentrates on common modelling frameworks for integrating the diverse fields of visual, audio, video, and
virtual world information.
MMM2004 deals with emerging Multimedia Modelling topics including:
• Multimedia Databases
• Audio Processing, Coding and Encryption
• Network Games and Animation
• Video Applications
• Multimedia Frameworks and QoS
• Topological and 3D Geometric Modelling
• Image Applications
• Image Retrieval
• Modelling / Editing / Virtual Environment
• Video Retrieval and Browsing

A scalable and extensible segment-event-object-based sports video retrieval system

Sport video data is growing rapidly as a result of the maturing digital technologies that support digital video capture, faster data processing, and large storage. However, (1) semi-automatic content extraction and annotation, (2) scalable indexing model, and (3) effective retrieval and browsing, still pose the most challenging problems for maximizing the usage of large video databases. This article will present the findings from a comprehensive work that proposes a scalable and extensible sports video retrieval system with two major contributions in the area of sports video indexing and retrieval. The first contribution is a new sports video indexing model that utilizes semi-schema-based indexing scheme on top of an Object-Relationship approach. This indexing model is scalable and extensible as it enables gradual index construction which is supported by ongoing development of future content extraction algorithms. The second contribution is a set of novel queries which are based on XQuery to generate dynamic and user-oriented summaries and event structures. The proposed sports video retrieval system has been fully implemented and populated with soccer, tennis, swimming, and diving video. The system has been evaluated against 20 users to demonstrate and confirm its feasibility and benefits. The experimental sports genres were specifically selected to represent the four main categories of sports domain: period-, set-point-, time (race)-, and performance-based sports. Thus, the proposed system should be generic and robust for all types of sports.

Content-based video indexing for sports applications using integrated multi-modal approach

This thesis presents a research work based on an integrated multi-modal approach for sports video indexing and retrieval. By combining specific features extractable from multiple (audio-visual) modalities, generic structure and specific events can be detected and classified. During browsing and retrieval, users will benefit from the integration of high-level semantic and some descriptive mid-level features such as whistle and close-up view of player(s). The main objective is to contribute to the three major components of sports video indexing systems. The first component is a set of powerful techniques to extract audio-visual features and semantic contents automatically. The main purposes are to reduce manual annotations and to summarize the lengthy contents into a compact, meaningful and more enjoyable presentation. The second component is an expressive and flexible indexing technique that supports gradual index construction. Indexing scheme is essential to determine the methods by which users can access a video database. The third and last component is a query language that can generate dynamic video summaries for smart browsing and support user-oriented retrievals.

Discovery of latent subcommunities in a blog's readership

The blogosphere has grown to be a mainstream forum of social interaction as well as a commercially attractive source of information and influence. Tools are needed to better understand how communities that adhere to individual blogs are constituted in order to facilitate new personal, socially-focused browsing paradigms, and understand how blog content is consumed, which is of interest to blog authors, big media, and search. We present a novel approach to blog subcommunity characterization by modeling individual blog readers using mixtures of an extension to the LDA family that jointly models phrases and time, Ngram Topic over Time (NTOT), and cluster with a number of similarity measures using Affinity Propagation. We experiment with two datasets: a small set of blogs whose authors provide feedback, and a set of popular, highly commented blogs, which provide indicators of algorithm scalability and interpretability without prior knowledge of a given blog. The results offer useful insight to the blog authors about their commenting community, and are observed to offer an integrated perspective on the topics of discussion and members engaged in those discussions for unfamiliar blogs. Our approach also holds promise as a component of solutions to related problems, such as online entity resolution and role discovery.

Sensing and using social context

We present online algorithms to extract social context: Social spheres are labeled locations of significance, represented as convex hulls extracted from GPS traces. Colocation is determined from Bluetooth and GPS to extract social rhythms, patterns in time, duration, place, and people corresponding to real-world activities. Social ties are formulated from proximity and shared spheres and rhythms. Quantitative evaluation is performed for 10+ million samples over 45 man-months. Applications are presented with assessment of perceived utility: Socio-Graph, a video and photo browser with filters for social metadata, and Jive, a blog browser that uses rhythms to discover similarity between entries automatically.

Video abstraction : a systematic review and classification

The demand for various multimedia applications is rapidly increasing due to the recent advance in the computing and network infrastructure, together with the widespread use of digital video technology. Among the key elements for the success of these applications is how to effectively and efficiently manage and store a huge amount of audio visual information, while at the same time providing user-friendly access to the stored data. This has fueled a quickly evolving research area known as video abstraction. As the name implies, video abstraction is a mechanism for generating a short summary of a video, which can either be a sequence of stationary images (keyframes) or moving images (video skims). In terms of browsing and navigation, a good video abstract will enable the user to gain maximum information about the target video sequence in a specified time constraint or sufficient information in the minimum time. Over past years, various ideas and techniques have been proposed towards the effective abstraction of video contents. The purpose of this article is to provide a systematic classification of these works. We identify and detail, for each approach, the underlying components and how they are addressed in specific works. © 2007 ACM.

Performance modelling of speculative prefetching for compound requests in low bandwidth networks

To improve the accuracy of access prediction, a prefetcher for web browsing should recognize the fact that a web page is a compound. By this term we mean that a user request for a single web page may require the retrieval of several multimedia items. Our prediction algorithm builds an access graph that captures the dynamics of web navigation rather than merely attaching probabilities to hypertext structure. When it comes to making prefetch decisions, most previous studies in speculative prefetching resort to simple heuristics, such as prefetching an item with access probabilities larger than a manually tuned threshold. The paper takes a different approach. Specifically, it models the performance of the prefetcher and develops a prefetch policy based on a theoretical analysis of the model. In the analysis, we derive a formula for the expected improvement in access time when prefetch is performed in anticipation for a compound request. We then develop an algorithm that integrates prefetch and cache replacement decisions so as to maximize this improvement. We present experimental results to demonstrate the effectiveness of compound-based prefetching in low bandwidth networks.

Identifying film takes for cinematic analysis

In this paper, we focus on the ‘reverse editing’ problem in movie analysis, i.e., the extraction of film takes, original camera shots that a film editor extracts and arranges to produce a finished scene. The ability to disassemble final scenes and shots into takes is essential for nonlinear browsing, content annotation and the extraction of higher order cinematic constructs from film. In this work, we investigate agglomerative hierachical clustering methods along with different similarity metrics and group distances for this task, and demonstrate our findings with 10 movies.

Towards a video browser for the digital native

Almost every aspect of how we create, transmit, and consume video has changed, but video interfaces still mimic those from video's inception. We extend Temporal Semantic Compression for interactive video browsing, which uses an arbitrary frame-by-frame interest measure to sub-sample video in real time, with user interface elements that visualize these measures and the effect of compressing on them. We experiment with a novel interest measure for popularity, and design novel visualizations for expressing interest measures and the compression interaction. We conduct the first formative evaluation of the TSC paradigm, with 8 subjects, and report design implications arising from it.

Detection on application layer DDoS using random walk model

Application Layer Distributed Denial of Service (ALDDoS) attacks have been increasing rapidly with the growth of Botnets and Ubiquitous computing. Differentiate to the former DDoS attacks, ALDDoS attacks cannot be efficiently detected, as attackers always adopt legitimate requests with real IP address, and the traffic has high similarity to legitimate traffic. In spite of that, we think, the attackers' browsing behavior will have great disparity from that of the legitimate users'. In this paper, we put forward a novel user behavior-based method to detect the application layer asymmetric DDoS attack. We introduce an extended random walk model to describe user browsing behavior and establish the legitimate pattern of browsing sequences. For each incoming browser, we observe his page request sequence and predict subsequent page request sequence based on random walk model. The similarity between the predicted and the observed page request sequence is used as a criterion to measure the legality of the user, and then attacker would be detected based on it. Evaluation results based on real collected data set has demonstrated that our method is very effective in detecting asymmetric ALDDoS attacks. © 2014 IEEE.

Failure to respond to food resource decline has catastrophic consequences for koalas in a high-density population in Southern Australia

Understanding the ability of koalas to respond to changes in their environment is critical for conservation of the species and their habitat. We monitored the behavioural response of koalas to declining food resources in manna gum (Eucalyptus viminalis) woodland at Cape Otway, Victoria, Australia, from September 2011 to November 2013. Over this period, koala population density increased from 10.1 to 18.4 koalas.ha-1. As a result of the high browsing pressure of this population, manna gum canopy condition declined with 71.4% manna gum being completely or highly defoliated in September 2013. Despite declining food resources, radio collared koalas (N = 30) exhibited high fidelity to small ranges (0.4-1.2 ha). When trees became severely defoliated in September 2013, koalas moved relatively short distances from their former ranges (mean predicted change in range centroid = 144 m) and remained in areas of 0.9 to 1.0 ha. This was despite the high connectivity of most manna gum woodland, and close proximity of the study site (< 3 km) to the contiguous mixed forest of the Great Otway National Park. Limited movement had catastrophic consequences for koalas with 71% (15/21) of radio collared koalas dying from starvation or being euthanased due to their poor condition between September and November 2013.

Fool me if you can: mimicking attacks and anti-attacks in cyberspace

Botnets have become major engines for malicious activities in cyberspace nowadays. To sustain their botnets and disguise their malicious actions, botnet owners are mimicking legitimate cyber behavior to fly under the radar. This poses a critical challenge in anomaly detection. In this paper, we use web browsing on popular web sites as an example to tackle this problem. First of all, we establish a semi-Markov model for browsing behavior. Based on this model, we find that it is impossible to detect mimicking attacks based on statistics if the number of active bots of the attacking botnet is sufficiently large (no less than the number of active legitimate users). However, we also find it is hard for botnet owners to satisfy the condition to carry out a mimicking attack most of the time. With this new finding, we conclude that mimicking attacks can be discriminated from genuine flash crowds using second order statistical metrics. We define a new fine correntropy metrics and show its effectiveness compared to others. Our real world data set experiments and simulations confirm our theoretical claims. Furthermore, the findings can be widely applied to similar situations in other research fields.

Bayesian nonparametric approaches to abnormality detection in video surveillance

In data science, anomaly detection is the process of identifying the items, events or observations which do not conform to expected patterns in a dataset. As widely acknowledged in the computer vision community and security management, discovering suspicious events is the key issue for abnormal detection in video surveil-lance. The important steps in identifying such events include stream data segmentation and hidden patterns discovery. However, the crucial challenge in stream data segmenta-tion and hidden patterns discovery are the number of coherent segments in surveillance stream and the number of traffic patterns are unknown and hard to specify. Therefore, in this paper we revisit the abnormality detection problem through the lens of Bayesian nonparametric (BNP) and develop a novel usage of BNP methods for this problem. In particular, we employ the Infinite Hidden Markov Model and Bayesian Nonparamet-ric Factor Analysis for stream data segmentation and pattern discovery. In addition, we introduce an interactive system allowing users to inspect and browse suspicious events.