Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Computer-assisted sampling of acoustic data for more efficient determination of bird species richness

Bird species richness survey is one of the most intriguing ecological topics for evaluating environmental health. Here, bird species richness denotes the number of unique bird species in a particular area. Factors affecting the investigation of bird species richness include weather, observation bias, and most importantly, the prohibitive costs of conducting surveys at large spatiotemporal scales. Thanks to advances in recording techniques, these problems have been alleviated by deploying sensors for acoustic data collection. Although automated detection techniques have been introduced to identify various bird species, the innate complexity of bird vocalizations, the background noise present in the recording and the escalating volumes of acoustic data pose a challenging task on determination of bird species richness. In this paper we proposed a two-step computer-assisted sampling approach for determining bird species richness in one-day acoustic data. First, a classification model is built based on acoustic indices for filtering out minutes that contain few bird species. Then the classified bird minutes are ordered by an acoustic index and the redundant temporal minutes are removed from the ranked minute sequence. The experimental results show that our method is more efficient in directing experts for determination of bird species compared with the previous methods.

Semi-supervised document clustering via loci

Document clustering is one of the prominent methods for mining important information from the vast amount of data available on the web. However, document clustering generally suffers from the curse of dimensionality. Providentially in high dimensional space, data points tend to be more concentrated in some areas of clusters. We take advantage of this phenomenon by introducing a novel concept of dynamic cluster representation named as loci. Clusters’ loci are efficiently calculated using documents’ ranking scores generated from a search engine. We propose a fast loci-based semi-supervised document clustering algorithm that uses clusters’ loci instead of conventional centroids for assigning documents to clusters. Empirical analysis on real-world datasets shows that the proposed method produces cluster solutions with promising quality and is substantially faster than several benchmarked centroid-based semi-supervised document clustering methods.

Using conceptual tool for intuitive interaction to design intuitive website for SME in India : A case study

Statistical reports of SMEs Internet usage from various countries indicate a steady growth. However, deeper investigation of SME’s e-commerce adoption and usage reveals that a number of SMEs fail to realize the full potential of e-commerce. Factors such as lack of tools and models in Information Systems and Information Technology for SMEs, and lack of technical expertise and specialized knowledge within and outside the SME have the most effect. This study aims to address the two important factors in two steps. First, introduce the conceptual tool for intuitive interaction. Second, explain the implementation process of the conceptual tool with the help of a case study. The subject chosen for the case study is a real estate SME from India. The design and development process of the website for the real estate SME was captured in this case study and the duration of the study was four months. Results indicated specific benefits for web designers and SME business owners. Results also indicated that the conceptual tool is easy to use without the need for technical expertise and specialized knowledge.

LibVM: An architecture for shared library sandboxing

Many software applications extend their functionality by dynamically loading libraries into their allocated address space. However, shared libraries are also often of unknown provenance and quality and may contain accidental bugs or, in some cases, deliberately malicious code. Most sandboxing techniques which address these issues require recompilation of the libraries using custom tool chains, require significant modifications to the libraries, do not retain the benefits of single address-space programming, do not completely isolate guest code, or incur substantial performance overheads. In this paper we present LibVM, a sandboxing architecture for isolating libraries within a host application without requiring any modifications to the shared libraries themselves, while still retaining the benefits of a single address space and also introducing a system call inter-positioning layer that allows complete arbitration over a shared library’s functionality. We show how to utilize contemporary hardware virtualization support towards this end with reasonable performance overheads and, in the absence of such hardware support, our model can also be implemented using a software-based mechanism. We ensure that our implementation conforms as closely as possible to existing shared library manipulation functions, minimizing the amount of effort needed to apply such isolation to existing programs. Our experimental results show that it is easy to gain immediate benefits in scenarios where the goal is to guard the host application against unintentional programming errors when using shared libraries, as well as in more complex scenarios, where a shared library is suspected of being actively hostile. In both cases, no changes are required to the shared libraries themselves.

Watching ourselves watching: Ethical issues in ethnographic action research

In this paper we explore some of the ethical issues associated with conducting Ethnographic Action Research (Tacchi, 2004; Tacchi et al., 2003) for understanding and facilitating distributed collaboration. Ethnography and action research are increasingly popular qualitative approaches to researching computer-supported collaboration and we are applying them together in a project within a distributed research centre. We identify ethical principles applied to the conduct of research in Australia and we briefly describe a number of ethical problems that arise due to the nature of Ethnographic Action Research.

4th International Workshop on Theory and Application of Visualizations and Human-centric Aspects in Processes

This is the fourth TAProViz workshop being run at the 13th International Conference on Business Process Management (BPM). The intention this year is to consolidate on the results of the previous successful workshops by further developing this important topic, identifying the key research topics of interest to the BPM visualization community. Towards this goal, the workshop topics were extended to human computer interaction and related domains. Submitted papers were evaluated by at least three program committee members, in a double blind manner, on the basis of significance, originality, technical quality and exposition. Three full and one position papers were accepted for presentation at the workshop. In addition, we invited a keynote speaker, Jakob Pinggera, a postdoctoral researcher at the Business Process Management Research Cluster at the University of Innsbruck, Austria.

Impact of automatic region-of-interest coding on perceived quality in mobile video

At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic region-of-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: - (1) automatic ROI by analyzing the visual contents automatically, and; - (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROI-based video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

Development and Simulation of a Variable Rate Controller for an Air search and Air Sampling Unmanned Aerial System

This report describes the development and simulation of a variable rate controller for a 6-degree of freedom nonlinear model. The variable rate simulation model represents an off the shelf autopilot. Flight experiment involves risks and can be expensive. Therefore a dynamic model to understand the performance characteristics of the UAS in mission simulation before actual flight test or to obtain parameters needed for the flight is important. The control and guidance is implemented in Simulink. The report tests the use of the model for air search and air sampling path planning. A GUI in which a set of mission scenarios, in which two experts (mission expert, i.e. air sampling or air search and an UAV expert) interact, is presented showing the benefits of the method.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Probabilistic load flow for distribution systems with uncertain PV generation

Large integration of solar Photo Voltaic (PV) in distribution network has resulted in over-voltage problems. Several control techniques are developed to address over-voltage problem using Deterministic Load Flow (DLF). However, intermittent characteristics of PV generation require Probabilistic Load Flow (PLF) to introduce variability in analysis that is ignored in DLF. The traditional PLF techniques are not suitable for distribution systems and suffer from several drawbacks such as computational burden (Monte Carlo, Conventional convolution), sensitive accuracy with the complexity of system (point estimation method), requirement of necessary linearization (multi-linear simulation) and convergence problem (Gram–Charlier expansion, Cornish Fisher expansion). In this research, Latin Hypercube Sampling with Cholesky Decomposition (LHS-CD) is used to quantify the over-voltage issues with and without the voltage control algorithm in the distribution network with active generation. LHS technique is verified with a test network and real system from an Australian distribution network service provider. Accuracy and computational burden of simulated results are also compared with Monte Carlo simulations.

Development and feasibility testing of an education program to improve knowledge and self-care among Aboriginal and Torres Strait Islander patients with heart failure

Background/Aim There is a 70% higher age-adjusted incidence of heart failure (HF) amongst Aboriginal and Torres Strait Islander people, three times more hospitalisations and twice as many deaths than non-Aboriginal people. There is a need to develop holistic yet individualised approaches in accord with the values of Aboriginal community healthcare to support patient education and self-care. The aim of this study was to re-design an existing HF educational resource (Fluid Watchers-Pacific Rim©) to be culturally safe for Aboriginal and Torres Strait Islander peoples, working in collaboration with the local community, and to conduct feasibility testing. Methods This study was conducted in two phases and utilised a mixed methods approach (qualitative and quantitative). Phase 1 of this study used action research methods to develop a culturally safe electronic resource to be provided to Aboriginal HF patients via a tablet computer. A HF expert panel adapted the existing resource to ensure it was evidence-based and contained appropriate language and images that reflects Aboriginal culture. A stakeholder group (which included Aboriginal workers and HF patients, as well as researchers and clinicians) then reviewed the resources and changes were made accordingly. In Phase 2, the new resource was tested on a sample of Aboriginal HF patients to assess feasibility and acceptability. Patient knowledge, satisfaction and self-care behaviours were measured using a before and after design with validated questionnaires. As this was a pilot test to determine feasibility, no statistical comparisons were made. Results - Phase 1: Throughout the process of resource development, two main themes emerged from the stakeholder consultation. These were the importance of identity, meaning that it was important to ensure that the resource accurately reflected the local community, with the appropriate clothing, skin tone and voice. The resource was adapted to reflect this and of the local community voiced the recordings for the resource. The other theme was comprehension; images were important and all text was converted to the first person and used plain language. - Phase 2: Five Aboriginal participants, mean age 61.6 ± 10.0 years, with NYHA Class III and IV heart failure were enrolled. Participants reported a high level of satisfaction with the resource (83.0%). HF knowledge (percentage of correct responses) increased from 48.0 ± 6.7% to 58.0 ± 9.7%, a 20.8% increase and results of the self-care index indicated that the biggest change was in patient confidence for self-care with a 95% increase in confidence score (46.7 ± 16.0 to 91.1 ± 11.5). Changes in management and maintenance scores varied between9275 patients. Conclusion By working in collaboration with HF experts, Aboriginal researchers and patients, a culturally safe HF resource has been developed for Aboriginal and Torres Strait Islander patients. Engaging Aboriginal researchers, capacity-building, and being responsive to local systems and structures enabled this pilot study to be successfully completed with the Aboriginal community and positive participant feedback demonstrated that the methodology used in this study was appropriate and acceptable; participants were able to engage with willingness and confidence.

The navigation and visualisation of environmental audio using zooming spectrograms

Acoustic recordings play an increasingly important role in monitoring terrestrial and aquatic environments. However, rapid advances in technology make it possible to accumulate thousands of hours of recordings, more than ecologists can ever listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from minutes, hours, days to years. The visualization should facilitate navigation and yield ecologically meaningful information prior to listening to the audio. To construct images, we calculate acoustic indices, statistics that describe the distribution of acoustic energy and reflect content of ecological interest. We combine various indices to produce false-color spectrogram images that reveal acoustic content and facilitate navigation. The technical challenge we investigate in this work is how to navigate recordings that are days or even months in duration. We introduce a method of zooming through multiple temporal scales, analogous to Google Maps. However, the “landscape” to be navigated is not geographical and not therefore intrinsically visual, but rather a graphical representation of the underlying audio. We describe solutions to navigating spectrograms that range over three orders of magnitude of temporal scale. We make three sets of observations: 1. We determine that at least ten intermediate scale steps are required to zoom over three orders of magnitude of temporal scale; 2. We determine that three different visual representations are required to cover the range of temporal scales; 3. We present a solution to the problem of maintaining visual continuity when stepping between different visual representations. Finally, we demonstrate the utility of the approach with four case studies.

Sequence variants in three loci influence monocyte counts and erythrocyte volume

Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.

Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.