Personalised information gathering and recommender systems : techniques and trends

With the explosive growth of resources available through the Internet, information mismatching and overload have become a severe concern to users. Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant and reliable information in a timely manner. Personalised information gathering and recommender systems represent state-of-the-art tools for efficient selection of the most relevant and reliable information resources, and the interest in such systems has increased dramatically over the last few years. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from a technological and social perspective. Aiming to promote high quality research in order to overcome these challenges, this paper provides a comprehensive survey on the recent work and achievements in the areas of personalised web information gathering and recommender systems. The report covers concept-based techniques exploited in personalised information gathering and recommender systems.

ClusterEval 1.0 : Cluster quality Evaluation software

This report describes the available functionality and use of the ClusterEval evaluation software. It implements novel and standard measures for the evaluation of cluster quality. This software has been used at the INEX XML Mining track and in the MediaEval Social Event Detection task.

Iris based identity verification robust to sample presentation security attacks

Iris based identity verification is highly reliable but it can also be subject to attacks. Pupil dilation or constriction stimulated by the application of drugs are examples of sample presentation security attacks which can lead to higher false rejection rates. Suspects on a watch list can potentially circumvent the iris based system using such methods. This paper investigates a new approach using multiple parts of the iris (instances) and multiple iris samples in a sequential decision fusion framework that can yield robust performance. Results are presented and compared with the standard full iris based approach for a number of iris degradations. An advantage of the proposed fusion scheme is that the trade-off between detection errors can be controlled by setting parameters such as the number of instances and the number of samples used in the system. The system can then be operated to match security threat levels. It is shown that for optimal values of these parameters, the fused system also has a lower total error rate.

Segmental torso masses and coronal plane joint torques in the adolescent scoliotic spine

Introduction. Calculating segmental (vertebral level-by-level) torso masses in Adolescent Idiopathic Scoliosis (AIS) patients allows the gravitational loading on the scoliotic spine during relaxed standing to be determined. This study used CT scans of AIS patients to measure segmental torso masses and explores how joint moments in the coronal plane are affected by changes in the position of the intervertebral joint’s axis of rotation; particularly at the apex of a scoliotic major curve. Methods. Existing low dose CT data from the Paediatric Spine Research Group was used to calculate vertebral level-by-level torso masses and joint torques occurring in the spine for a group of 20 female AIS patients (mean age 15.0 ± 2.7 years, mean Cobb angle 53 ± 7.1°). Image processing software, ImageJ (v1.45 NIH USA) was used to threshold the T1 to L5 CT images and calculate the segmental torso volume and mass corresponding to each vertebral level. Body segment masses for the head, neck and arms were taken from published anthropometric data. Intervertebral (IV) joint torques at each vertebral level were found using principles of static equilibrium together with the segmental body mass data. Summing the torque contributions for each level above the required joint, allowed the cumulative joint torque at a particular level to be found. Since there is some uncertainty in the position of the coronal plane Instantaneous Axis of Rotation (IAR) for scoliosis patients, it was assumed the IAR was located in the centre of the IV disc. A sensitivity analysis was performed to see what effect the IAR had on the joint torques by moving it laterally 10mm in both directions. Results. The magnitude of the torso masses from T1-L5 increased inferiorly, with a 150% increase in mean segmental torso mass from 0.6kg at T1 to 1.5kg at L5. The magnitudes of the calculated coronal plane joint torques during relaxed standing were typically 5-7 Nm at the apex of the curve, with the highest apex joint torque of 7Nm being found in patient 13. Shifting the assumed IAR by 10mm towards the convexity of the spine, increased the joint torque at that level by a mean 9.0%, showing that calculated joint torques were moderately sensitive to the assumed IAR location. When the IAR midline position was moved 10mm away from the convexity of the spine, the joint torque reduced by a mean 8.9%. Conclusion. Coronal plane joint torques as high as 7Nm can occur during relaxed standing in scoliosis patients, which may help to explain the mechanics of AIS progression. This study provides new anthropometric reference data on vertebral level-by-level torso mass in AIS patients which will be useful for biomechanical models of scoliosis progression and treatment. However, the CT scans were performed in supine (no gravitational load on spine) and curve magnitudes are known to be smaller than those measured in standing.

Monte Carlo verification of intensity modulated radiotherapy treatments using EPIDS

Purpose: Electronic Portal Imaging Devices (EPIDs) are available with most linear accelerators (Amonuk, 2002), the current technology being amorphous silicon flat panel imagers. EPIDs are currently used routinely in patient positioning before radiotherapy treatments. There has been an increasing interest in using EPID technology tor dosimetric verification of radiotherapy treatments (van Elmpt, 2008). A straightforward technique involves the EPID panel being used to measure the fluence exiting the patient during a treatment which is then compared to a prediction of the fluence based on the treatment plan. However, there are a number of significant limitations which exist in this Method: Resulting in a limited proliferation ot this technique in a clinical environment. In this paper, we aim to present a technique of simulating IMRT fields using Monte Carlo to predict the dose in an EPID which can then be compared to the measured dose in the EPID. Materials: Measurements were made using an iView GT flat panel a-SI EPfD mounted on an Elekta Synergy linear accelerator. The images from the EPID were acquired using the XIS software (Heimann Imaging Systems). Monte Carlo simulations were performed using the BEAMnrc and DOSXVZnrc user codes. The IMRT fieids to be delivered were taken from the treatment planning system in DICOMRT format and converted into BEAMnrc and DOSXYZnrc input files using an in-house application (Crowe, 2009). Additionally. all image processing and analysis was performed using another in-house application written using the Interactive Data Language (IDL) (In Visual Information Systems). Comparison between the measured and Monte Carlo EPID images was performed using a gamma analysis (Low, 1998) incorporating dose and distance to agreement criteria. Results: The fluence maps recorded by the EPID were found to provide good agreement between measured and simulated data. Figure 1 shows an example of measured and simulated IMRT dose images and profiles in the x and y directions. "A technique for the quantitative evaluation of dose distributions", Med Phys, 25(5) May 1998 S. Crowe, 1. Kairn, A. Fielding, "The Development of a Monte Carlo system to verify Radiotherapy treatment dose calculations", Radiotherapy & Oncology, Volume 92, Supplement 1, August 2009, Pages S71-S71.

An algorithm to cluster the spectra in a spectrogram

The work described in this technical report is part of an ongoing project at QUT to build practical tools for the manipulation, analysis and visualisation of recordings of the natural environment. This report describes the algorithm we use to cluster the spectra in a spectrogram. The report begins with a brief description of the signal processing that prepares the spectrograms.

Aircraft collision avoidance using spherical visual predictive control and single point features

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

Counterfeiting attacks on block-wise dependent fragile watermarking schemes

In this paper, we present three counterfeiting attacks on the block-wise dependent fragile watermarking schemes. We consider vulnerabilities such as the exploitation of a weak correlation among block-wise dependent watermarks to modify valid watermarked %(medical or other digital) images, where they could still be verified as authentic, though they are actually not. Experimental results successfully demonstrate the practicability and consequences of the proposed attacks for some relevant schemes. The development of the proposed attack models can be used as a means to systematically examine the security levels of similar watermarking schemes.

Segmental torso masses and gravity-induced coronal plane joint moments in adolescent idiopathic scoliosis

Introduction: Calculating segmental (vertebral level-by-level) torso masses in Adolescent Idiopathic Scoliosis (AIS) patients allows the gravitational loading on the scoliotic spine during relaxed standing to be estimated. This study used supine CT scans of AIS patients to measure segmental torso masses and explored the joint moments in the coronal plane, particularly at the apex of a scoliotic major curve. Methods: Existing low dose CT data from the Paediatric Spine Research Group was used to calculate vertebral level-by-level torso masses and joint moments occurring in the spine for a group of 20 female AIS patients with right sided thoracic curves. The mean age was 15.0 ± 2.7 years and all curves were classified Lenke Type 1 with a mean Cobb angle 52 ± 5.9°. Image processing software, ImageJ (v1.45 NIH USA) was used to create reformatted coronal plane images, reconstruct vertebral level-by-level torso segments and subsequently measure the torso volume corresponding to each vertebral level. Segment mass was then determined by assuming a tissue density of 1.04x103 kg/m3. Body segment masses for the head, neck and arms were taken from published anthropometric data (Winter 2009). Intervertebral joint moments in the coronal plane at each vertebral level were found from the position of the centroid of the segment masses relative to the joint centres with the segmental body mass data. Results and Discussion: The magnitude of the torso masses from T1-L5 increased inferiorly, with a 150% increase in mean segmental torso mass from 0.6kg at T1 to 1.5kg at L5. The magnitudes of the calculated coronal plane joint moments during relaxed standing were typically 5-7 Nm at the apex of the curve, with the highest apex joint torque of 7Nm. The CT scans were performed in the supine position and curve magnitudes are known to be 7-10° smaller than those measured in standing, due to the absence of gravity acting on the spine. Hence, it can be expected that the moments produced by gravity in the standing individual will be greater than those calculated here.

Numerical simulation of anomalous diffusion with application to medical imaging

The first objective of this project is to develop new efficient numerical methods and supporting error and convergence analysis for solving fractional partial differential equations to study anomalous diffusion in biological tissue such as the human brain. The second objective is to develop a new efficient fractional differential-based approach for texture enhancement in image processing. The results of the thesis highlight that the fractional order analysis captured important features of nuclear magnetic resonance (NMR) relaxation and can be used to improve the quality of medical imaging.

Detecting anomalous events at railway level crossings

Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

Rank minimization across appearance and shape for AAM ensemble fitting

Active Appearance Models (AAMs) employ a paradigm of inverting a synthesis model of how an object can vary in terms of shape and appearance. As a result, the ability of AAMs to register an unseen object image is intrinsically linked to two factors. First, how well the synthesis model can reconstruct the object image. Second, the degrees of freedom in the model. Fewer degrees of freedom yield a higher likelihood of good fitting performance. In this paper we look at how these seemingly contrasting factors can complement one another for the problem of AAM fitting of an ensemble of images stemming from a constrained set (e.g. an ensemble of face images of the same person).

An exploratory study of the potential of resurfacing articular cartilage with synthetic phospholipids

This thesis is aimed at further understanding the uppermost lipid-filled membranous layer (i.e. surface amorphous layer (SAL)) of articular cartilage and to develop a scientific framework for re-introducing lipids onto the surface of lipid-depleted articular cartilage (i.e. "resurfacing"). The outcome will potentially contribute to knowledge that will facilitate the repair of the articular surface of cartilage where degradation is limited to the loss of the lipids of the SAL only. The surface amorphous layer is of utmost importance to the effective load-spreading, lubrication, and semipermeability (which controls its fluid management, nutrient transport and waste removal) of articular cartilage in the mammalian joints. However, because this uppermost layer of cartilage is often in contact during physiological function, it is prone to wear and tear, and thus, is the site for damage initiation that can lead to the early stages of joint condition like osteoarthritis, and related conditions that cause pain and discomfort leading to low quality of life in patients. It is therefore imperative to conduct a study which offers insight into remedying this problem. It is hypothesized that restoration (resurfacing) of the surface amorphous layer can be achieved by re-introducing synthetic surface-active phospholipids (SAPL) into the joint space. This hypothesis was tested in this thesis by exposing cartilage samples whose surface lipids had been depleted to individual and mixtures of synthetic saturated and unsaturated phospholipids. The surfaces of normal, delipidized, and relipidized samples of cartilage were characterized for their structural integrity and functionality using atomic force microscope (AFM), confocal microscope (COFM), Raman spectroscopy, magnetic resonance imaging (MRI) with image processing in the MATLAB® environment and mechanical loading experiments. The results from AFM imaging, confocal microscopy, and Raman spectroscopy revealed a successful deposition of new surface layer on delipidized cartilage when incubated in synthetic phospholipids. The relipidization resulted in a significant improvement in the surface nanostructure of the artificially degraded cartilage, with the complete SAPL mixture providing better outcomes in comparison to those created with the single SAPL components (palmitoyl-oleoyl-phosphatidylcholine, POPC and dipalmitoyl-phosphatidylcholine, DPPC). MRI analysis revealed that the surface created with the complete mixture of synthetic lipids was capable of providing semipermeability to the surface layer of the treated cartilage samples relative to the normal intact surface. Furthermore, deformation energy analysis revealed that the treated samples were capable of delivering the elastic properties required for load bearing and recovery of the tissue relative to the normal intact samples, with this capability closer between the normal and the samples incubated in the complete lipid mixture. In conclusion, this thesis has established that it is possible to deposit/create a potentially viable layer on the surface of cartilage following degradation/lipid loss through incubation in synthetic lipid solutions. However, further studies will be required to advance the ideas developed in this thesis, for the development of synthetic lipid-based injections/drugs for treatment of osteoarthritis and other related joint conditions.

Vision-based estimation of airborne target pseudobearing rate using hidden Markov model filters

The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information.