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.

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.

A computer code for enclosed natural convection in the boundary layer regime

A computer code is developed for the numerical prediction of natural convection in rectangular two-dimensional cavities at high Rayleigh numbers. The governing equations are retained in the primitive variable form. The numerical method is based on finite differences and an ADI scheme. Convective terms may be approximated with either central or hybrid differencing for greater stability. A non-uniform grid distribution is possible for greater efficiency. The pressure is dealt with via a SIMPLE type algorithm and the use of a fast elliptic solver for the solenoidal velocity correction field significantly reduces computing times. Preliminary results indicate that the code is reasonably accurate, robust and fast compared with existing benchmarks and finite difference based codes, particularly at high Rayleigh numbers. Extension to three-dimensional problems and turbulence studies in similar geometries is readily possible and indicated.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

Animated Mise-en-scene and aesthetic harmony: An expansion of the traditional principles of animation to 3D computer animation

3D Computer Graphics (CG) has become the dominant medium for modern animated feature films. It is widely understood that traditional principles of animation developed in the 1930s at the Walt Disney Studio remain applicable to this new medium and heavily influence the range of aesthetic motion styles in contemporary animation. Via a frame-by-frame textual analysis of four animated feature films, this thesis tests and confirms the validity of the principles of animation and expands upon them by reinterpreting the Disney principle of appeal as aesthetic harmony, which delineates the way in which character posing and transitions between poses contribute to the animated motion styles that animators work in today.

Project Energise: Using participatory approaches and real time computer prompts to reduce occupational sitting and increase work time physical activity in office workers

Objectives This efficacy study assessed the added impact real time computer prompts had on a participatory approach to reduce occupational sedentary exposure and increase physical activity. Design Quasi-experimental. Methods 57 Australian office workers (mean [SD]; age = 47 [11] years; BMI = 28 [5] kg/m2; 46 men) generated a menu of 20 occupational ‘sit less and move more’ strategies through participatory workshops, and were then tasked with implementing strategies for five months (July–November 2014). During implementation, a sub-sample of workers (n = 24) used a chair sensor/software package (Sitting Pad) that gave real time prompts to interrupt desk sitting. Baseline and intervention sedentary behaviour and physical activity (GENEActiv accelerometer; mean work time percentages), and minutes spent sitting at desks (Sitting Pad; mean total time and longest bout) were compared between non-prompt and prompt workers using a two-way ANOVA. Results Workers spent close to three quarters of their work time sedentary, mostly sitting at desks (mean [SD]; total desk sitting time = 371 [71] min/day; longest bout spent desk sitting = 104 [43] min/day). Intervention effects were four times greater in workers who used real time computer prompts (8% decrease in work time sedentary behaviour and increase in light intensity physical activity; p < 0.01). Respective mean differences between baseline and intervention total time spent sitting at desks, and the longest bout spent desk sitting, were 23 and 32 min/day lower in prompt than in non-prompt workers (p < 0.01). Conclusions In this sample of office workers, real time computer prompts facilitated the impact of a participatory approach on reductions in occupational sedentary exposure, and increases in physical activity.

Orienting to emotion in computer-mediated Cognitive Behavioural Therapy

Exploring emotions is a defining feature of psychotherapy. This study explores how therapists explore emotions when they cannot see or hear their clients. In analysing 1,279 sessions of online text-based Cognitive Behavioural Therapy (CBT) we focused on therapists’ commiserations (e.g., “I’m sorry to hear that”) and their affective inferences (e.g., “that sounds very scary for you”). Both practices routinely prefaced moves to pursue a range of therapeutic activities, many of which did not prioritise sustained focus on the emotion that had just been oriented to. By separating message composition from message transmission, the modality used for these therapy sessions enabled therapists to combine orientations to emotion with attempts to shift the focus of discussion. Our analysis finds that although physically co-present and computer-mediated psychotherapy share a common focus on emotional experience, the modality used for therapy can be relevant in the design and use of these orientations. Data are in British English.