Automatic particle picking of biological molecules imaged by electron microscopy

One of the next great challenges of cell biology is the determination of the enormous number of protein structures encoded in genomes. In recent years, advances in electron cryo-microscopy and high-resolution single particle analysis have developed to the point where they now provide a methodology for high resolution structure determination. Using this approach, images of randomly oriented single particles are aligned computationally to reconstruct 3-D structures of proteins and even whole viruses. One of the limiting factors in obtaining high-resolution reconstructions is obtaining a large enough representative dataset ($>100,000$ particles). Traditionally particles have been manually picked which is an extremely labour intensive process. The problem is made especially difficult by the low signal-to-noise ratio of the images. This paper describes the development of automatic particle picking software, which has been tested with both negatively stained and cryo-electron micrographs. This algorithm has been shown to be capable of selecting most of the particles, with few false positives. Further work will involve extending the software to detect differently shaped and oriented particles.

Visual sea-floor mapping from low overlap imagery using bi-objective bundle adjustment and constrained motion

In most visual mapping applications suited to Autonomous Underwater Vehicles (AUVs), stereo visual odometry (VO) is rarely utilised as a pose estimator as imagery is typically of very low framerate due to energy conservation and data storage requirements. This adversely affects the robustness of a vision-based pose estimator and its ability to generate a smooth trajectory. This paper presents a novel VO pipeline for low-overlap imagery from an AUV that utilises constrained motion and integrates magnetometer data in a bi-objective bundle adjustment stage to achieve low-drift pose estimates over large trajectories. We analyse the performance of a standard stereo VO algorithm and compare the results to the modified vo algorithm. Results are demonstrated in a virtual environment in addition to low-overlap imagery gathered from an AUV. The modified VO algorithm shows significantly improved pose accuracy and performance over trajectories of more than 300m. In addition, dense 3D meshes generated from the visual odometry pipeline are presented as a qualitative output of the solution.

The assessment of students with disabilities : the Australian law as to reasonable adjustment and academic integrity

This paper explains the legislation which underpins the right to reasonable adjustment in education for students with disabilities in Australian schools. It gives examples of the kinds of adjustment which may be made to promote equality of opportunity in the area of assessment. It also considers how the law has constructed the border between reasonable adjustment and academic integrity.

Timed and Probabilistic Automata for Automatic Animal Call Recognition

Automatic Call Recognition is vital for environmental monitoring. Patten recognition has been applied in automatic species recognition for years. However, few studies have applied formal syntactic methods to species call structure analysis. This paper introduces a novel method to adopt timed and probabilistic automata in automatic species recognition based upon acoustic components as the primitives. We demonstrate this through one kind of birds in Australia: Eastern Yellow Robin.

Automatic Audio Segmentation Using the Generalized Likelihood Ratio

This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.

Posttraumatic growth and posttraumatic depreciation as predictors of psychological adjustment

Informed by current trauma literature, this study explored the relationships between Posttraumatic Growth (PTG; Tedeschi & Calhoun, 1995), Posttraumatic Depreciation (PTD; Cann et al., 2010) and other post-trauma outcomes including well-being, psychological flourishing, and psychological distress. The predictive utility of PTG and PTD was also examined. The sample comprised 104 trauma survivors who completed the Posttraumatic Growth Inventory – 42 (Baker et al., 2008) and several outcome measures. As expected, PTD showed strong linear correlations with well-being, flourishing and distress, and emerged as a significant predictor of scores on such measures. However, PTG showed negligible correlations with well-being, flourishing and distress. This reaffirms that PTG and PTD measure conceptually distinct and independent dimensions of experience, which has implications for therapeutic practice.

Using static analysis for automatic assessment and mitigation of unwanted and malicious activities within Android applications

In the last decade, smartphones have gained widespread usage. Since the advent of online application stores, hundreds of thousands of applications have become instantly available to millions of smart-phone users. Within the Android ecosystem, application security is governed by digital signatures and a list of coarse-grained permissions. However, this mechanism is not fine-grained enough to provide the user with a sufficient means of control of the applications' activities. Abuse of highly sensible private information such as phone numbers without users' notice is the result. We show that there is a high frequency of privacy leaks even among widely popular applications. Together with the fact that the majority of the users are not proficient in computer security, this presents a challenge to the engineers developing security solutions for the platform. Our contribution is twofold: first, we propose a service which is able to assess Android Market applications via static analysis and provide detailed, but readable reports to the user. Second, we describe a means to mitigate security and privacy threats by automated reverse-engineering and refactoring binary application packages according to the users' security preferences.

The relationship between self-esteem and psychological adjustment in young adolescents

The study adopts a multi-dimensional construct of self-esteem to examine the relationship between self-perception and psychological adjustment in order to identify specific dimensions that discriminate between disturbed and non-disturbed groups. The disturbed group (n = 33) is derived from a clinical sample and are matched with a non-disturbed group (n = 33) of adolescents. Results indicate that dimensional self-concept scores are significantly lower for clinical subjects while there are no significant differences between groups on the mathematics, honesty, and physical ability dimensions. These findings provide a more fine grained understanding of the relationship between self-esteem and psychological adjustment and emphasize the need to examine self-esteem in terms of its particular dimensions.

Social adjustment and symptomatology in two types of homeless adolescents : runaways and throwaways

Previous research on homeless adolescents has largely ignored the distinction between those who have left home on their volition (runaways) and those who have been forced to leave (throwaways). Fifty-two homeless adolescents in Brisbane, Australia, were assessed to compare male and female runaways and throwaways for social adjustment and symptomatology. Differences for social adjustment (antisocial tendencies and aggression) and symptomatology (social isolation and depression) were predicted. Results indicated that male runaways were significantly more hostile than male throwaways (p < 0,001), and significantly more socially isolated than female runaways (p < 0,025). Female throwaways, however, were significantly more hostile than male throwaways (p < 0,025) and female runaways (p < 0,025). Yet homeless males overall had a significantly stronger urge to act out hostility than homeless females (p < 0,025). In addition, female throwaways were significantly more antisocial than male throwaways (p < 0,001). There were no significant differences for depression. A theory of inner social control (Hirschi, 1969), postulating absence of bonding in earlier socialization, was supported.

Effects of eco-driving instructions using a vehicle with automatic transmission on urban roads

Eco-driving instructions could reduce fuel consumption to up to 20% (EcoMove, 2010). Participants (N=13) drove an instrumented vehicle (i.e. Toyota Camry 2007) with an automatic transmission. Fuel consumption of the participants were compared before and after they received eco-driving instructions. Participants drove the same vehicle on the same urban route under similar traffic conditions. Results show that, on free flow sections of the track, all participants drove slightly faster (on average, 0.7 Km/h faster), during the lap for which they were instructed to drive in an eco-friendly manner as compared to when they were not given the eco-driving instruction. Suprisingly, eco-driving instructions increased the RPM significantly in most cases. Fuel consumption slightly decreased (6%) after the eco-driving instructions. We have found strong evidence showing that the fuel saving observed in our experiment (urban environment, automatic transmission) fall short of the 20% reduction claimed in other international trials.

Robust automatic speaker linking and attribution

This research makes a major contribution which enables efficient searching and indexing of large archives of spoken audio based on speaker identity. It introduces a novel technique dubbed as “speaker attribution” which is the task of automatically determining ‘who spoke when?’ in recordings and then automatically linking the unique speaker identities within each recording across multiple recordings. The outcome of the research will also have significant impact in improving the performance of automatic speech recognition systems through the extracted speaker identities.

Automatic query expansion : a structural linguistic perspective

A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

Non-linear position control for hover and automatic landing of unmanned aerial vehicles

This study presents a disturbance attenuation controller for horizontal position stabilisation for hover and automatic landings of a rotary-wing unmanned aerial vehicle (RUAV) operating close to the landing deck in rough seas. Based on a helicopter model representing aerodynamics during the landing phase, a non-linear state feedback H∞ controller is designed to achieve rapid horizontal position tracking in a gusty environment. Practical constraints including flapping dynamics, servo dynamics and time lag effect are considered. A high-fidelity closed-loop simulation using parameters of the Vario XLC gas-turbine helicopter verifies performance of the proposed horizontal position controller. The proposed controller not only increases the disturbance attenuation capability of the RUAV, but also enables rapid position response when gusts occur. Comparative studies show that the H∞ controller exhibits performance improvement and can be applied to ship/RUAV landing systems.

Monotonous trend estimation of deck displacement for automatic landing of rotorcraft UAVs

This paper presents a novel and practical procedure for estimating the mean deck height to assist in automatic landing operations of a Rotorcraft Unmanned Aerial Vehicle (RUAV) in harsh sea environments. A modified Prony Analysis (PA) procedure is outlined to deal with real-time observations of deck displacement, which involves developing an appropriate dynamic model to approach real deck motion with parameters identified through implementing the Forgetting Factor Recursive Least Square (FFRLS) method. The model order is specified using a proper order-selection criterion based on minimizing the summation of accumulated estimation errors. In addition, a feasible threshold criterion is proposed to separate the dominant components of deck displacement, which results in an accurate instantaneous estimation of the mean deck position. Simulation results demonstrate that the proposed recursive procedure exhibits satisfactory estimation performance when applied to real-time deck displacement measurements, making it well suited for integration into ship-RUAV approach and landing guidance systems.