Topical pattern based document modelling and relevance ranking

For traditional information filtering (IF) models, it is often assumed that the documents in one collection are only related to one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling was proposed to generate statistical models to represent multiple topics in a collection of documents, but in a topic model, topics are represented by distributions over words which are limited to distinctively represent the semantics of topics. Patterns are always thought to be more discriminative than single terms and are able to reveal the inner relations between words. This paper proposes a novel information filtering model, Significant matched Pattern-based Topic Model (SPBTM). The SPBTM represents user information needs in terms of multiple topics and each topic is represented by patterns. More importantly, the patterns are organized into groups based on their statistical and taxonomic features, from which the more representative patterns, called Significant Matched Patterns, can be identified and used to estimate the document relevance. Experiments on benchmark data sets demonstrate that the SPBTM significantly outperforms the state-of-the-art models.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Is the sun too bright in Queensland? An approach to robust outdoor colour beacon detection

Using cameras onboard a robot for detecting a coloured stationary target outdoors is a difficult task. Apart from the complexity of separating the target from the background scenery over different ranges, there are also the inconsistencies with direct and reflected illumination from the sun,clouds, moving and stationary objects. They can vary both the illumination on the target and its colour as perceived by the camera. In this paper, we analyse the effect of environment conditions, range to target, camera settings and image processing on the reported colours of various targets. The analysis indicates the colour space and camera configuration that provide the most consistent colour values over varying environment conditions and ranges. This information is used to develop a detection system that provides range and bearing to detected targets. The system is evaluated over various lighting conditions from bright sunlight, shadows and overcast days and demonstrates robust performance. The accuracy of the system is compared against a laser beacon detector with preliminary results indicating it to be a valuable asset for long-range coloured target detection.

Pattern-based topic modelling and its application for information filtering and information retrieval

This thesis targets on a challenging issue that is to enhance users' experience over massive and overloaded web information. The novel pattern-based topic model proposed in this thesis can generate high-quality multi-topic user interest models technically by incorporating statistical topic modelling and pattern mining. We have successfully applied the pattern-based topic model to both fields of information filtering and information retrieval. The success of the proposed model in finding the most relevant information to users mainly comes from its precisely semantic representations to represent documents and also accurate classification of the topics at both document level and collection level.

Searching for people using semantic soft biometric descriptions

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to communicate and easy to understand. However such queries are not easily utilised within intelligent video surveillance systems, as they are difficult to transform into a representation that can be utilised by computer vision algorithms. In this paper we propose a novel approach that transforms such a semantic query into an avatar in the form of a channel representation that is searchable within a video stream. We show how spatial, colour and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter like approach. We demonstrate state-of-the-art performance for locating a subject in video based on a description, achieving a relative performance improvement of 46.7% over the baseline. We also apply this approach to person re-detection, and show that the approach can be used to re-detect a person in a video steam without the use of person detection.

Mauve: How one man invented the colour that changed the world

In an essay, "The Books of Last Things", Delia Falconer discusses the emergence of a new genre in publishing - microhistories. She cites a number of recent titles in non-fiction and fiction - Longitude, Cod, Tulips, Pushkin's Button, Nathaniel's Nutmeg, Zarafa, The Surgeon of Crowthorne, The Potato, The Perfect Storm. Delia Falconer observes of this tradition: "One has the sense, reading these books, of a surprising weight, of pleasant shock. In part, it is because we are looking at things which are generally present around us, but modestly out of sight and mind - historical nitty gritty like cod, potatoes, longitudinal clocks - which the authors have thrust suddenly, like a Biblical visitation of frogs or locusts, in our face. Things like spice and buttons and clocks are generally seen to enable history on the large scale, but are not often viewed as its worthy subjects. And by the same grand logic of history, more unusual phenomena like cabinets of curiosities or glass-making or farm lore or sailors' knots are simply odd blips on its radar screen, interesting footnotes. These new books, microhistories, reverse the usual order of history, which argues from the general to the particular, in order to prove its inevitable progress. They start from the footnotes. But by reversing the process, and walking through the back door of history, you don't necessarily end up at the front of the same house." Delia Falconer speculates about the reasons for the popularity of microhistories. She concludes: "I would like to think that reading them is not simply an exercise in nostalgia, but a challenge to the present". In Mauve, Simon Garfield provides a new way of thinking and writing about the history of intellectual property. Instead of providing a grand historical narrative of intellectual property, he tells the story of a particular invention, and its exploitation. Simon Garfield relates how English chemist William Perkin accidentally discovered a way to mass-produce colour mauve in a factory. Working on a treatment for malaria in his London home laboratory, Perkin failed to produce artificial quinine. Instead he created a dark oily sludge that turned silk a beautiful light purple. The colour was unique and became the most desirable shade in the fashion houses of Paris and London. ... The book Mauve will have a number of contemporary resonances for intellectual property lawyers and academics. Simon Garfield emphasizes the difficulties inherent in commercialising an invention and managing intellectual property. He investigates the uneasy collaboration between industry and science. Simon Garfield suggests that complaints about the efficacy of patent offices are perennial. He also highlights the problems faced by courts and law-makers in accommodating new technologies within the logic of patent law. In his elegant microhistory of the colour mauve, Simon Garfield confirms the conclusion of Brad Sherman and Lionel Bently that many aspects of modern intellectual property law can only be understood through an understanding of the past: "The image of intellectual property law that developed during the 19th century and the narrative of identity which this engendered played and continue to play an important role in the way we think about and understand intellectual property law".

Geographical and morphological variation within and between colour phases in Coris julis (L. 1758), a protogynous marine fish

The possible differences between sexes in patterns of morphological variation in geographical space have been explored only in gonochorist freshwater species. We explored patterns of body shape variation in geographical space in a marine sequential hermaphrodite species, Coris julis (L. 1758), analyzing variation both within and between colour phases, through the use of geometric morphometrics and spatially-explicit statistical analyses. We also tested for the association of body shape with two environmental variables: temperature and chlorophyll a concentration, as obtained from time-series of satellite-derived data. Both colour phases showed a significant morphological variation in geographical space and patterns of variation divergent between phases. Although the morphological variation was qualitatively similar, individuals in the initial colour phase showed a more marked variation than individuals in the terminal phase. Body shape showed a weak but significant correlation with environmental variables, which was more pronounced in primary specimens.

Body shape variation and colour change during growth in a protogynous fish

Protogynous sequential hermaphroditism is very common in marine fish. Despite a large number of studies on various aspects of sequential hermaphroditism in fish, the relationship between body shape and colour during growth in dichromatic species has not been assessed. Using geometric morphometrics, the present study explores the relationship between growth, body shape and colouration in Coris julis (L. 1758), a small protogynous labrid species with distinct colour phases. Results show that body shape change during growth is independent of change in colour phase, a result which can be explained by the biology of the species and by the social control of sex change. Also, during growth the body grows deeper and the head has a steeper profile. It is hypothesized that a deeper body and a steeper profile might have a function in agonistic interactions between terminal phase males and that the marked chromatic difference between colour phases allows the lack of strict interdependence of body shape and colour during growth.

Spatiotemporal pattern of bacillary dysentery in China from 1990 to 2009: What is the driver behind?

BACKGROUND Little is known about the spatiotemporal pattern of bacillary dysentery (BD) in China. This study assessed the geographic distribution and seasonality of BD in China over the past two decades. METHODS Data on monthly BD cases in 31 provinces of China from January 1990 to December 2009 obtained from Chinese Center for Disease Control and Prevention, and data on demographic and geographic factors, as well as climatic factors, were compiled. The spatial distributions of BD in the four periods across different provinces were mapped, and heat maps were created to present the seasonality of BD by geography. A cosinor function combined with Poisson regression was used to quantify the seasonal parameters of BD, and a regression analysis was conducted to identify the potential drivers of morbidity and seasonality of BD. RESULTS Although most regions of China have experienced considerable declines in BD morbidity over the past two decades, Beijing and Ningxia still had high BD morbidity in 2009. BD morbidity decreased more slowly in North-west China than other regions. BD in China mainly peaked from July to September, with heterogeneity in peak time between regions. Relative humidity was associated with BD morbidity and peak time, and latitude was the major predictor of BD amplitude. CONCLUSIONS The transmission of BD was heterogeneous in China. Improved sanitation and hygiene in North-west China, and better access to clean water and food in the big floating population in some metropolises could be the focus of future preventive interventions against BD. BD control efforts should put more emphasis on those dry areas in summer.

Dynamic pattern of suicide in Australia, 1986-2005: A descriptive-analytic study

Objective This study explores the spatiotemporal variations of suicide across Australia from 1986 to 2005, discusses the reasons for dynamic changes, and considers future suicide research and prevention strategies. Design Suicide (1986–2005) and population data were obtained from the Australian Bureau of Statistics. A series of analyses were conducted to examine the suicide pattern by sex, method and age group over time and geography. Results Differences in suicide rates across sex, age groups and suicide methods were found across geographical areas. Male suicides were mainly completed by hanging, firearms, gases and self-poisoning. Female suicides were primarily completed by hanging and self-poisoning. Suicide rates were higher in rural areas than in urban areas (capital cities and regional centres). Suicide rates by firearms were higher in rural areas than in urban areas, while the pattern for self-poisoning showed the reverse trend. Suicide rates had relatively stable trend for the total population and those aged between 15 and 54, while suicide decreased among 55 years and over during the study period. There was a decrease in suicides by firearms during the study period especially after 1996 when a new firearm control law was implemented, while suicide by hanging continued to increase. Areas with a high proportion of indigenous population (eg, northwest of Queensland and top north of the Northern Territory) had shown a substantial increase in suicide incidence after 1995. Conclusions Suicide rates varied over time and space and across sexes, age groups and suicide methods. This study provides detailed patterns of suicide to inform suicide control and prevention strategies for specific subgroups and areas of high and increased risk.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Xylan-Degrading Enzymes from the Thermophilic Fungus Humicola Zanuginosa (Griffon and Maublanc) Bunce: Action Pattern of Xylanase and beta-Glucosidase on Xylans, Xylooligomers and Arabinoxylooligomers

The mode of action of xylanase and beta-glucosidase purified from the culture filtrate of Humicola lanuginosa (Griffon and Maublanc) Bunce on the xylan extracted from sugarcane bagasse and on two commercially available larchwood and oat spelt xylans, on xylooligomers and on arabinoxylooligomers was studied. While larchwood and oat spelt xylans were hydrolyzed to the same extent in 24 h, sugarcane bagasse xylan was hydrolyzed to a lesser extent in the same period. It was found that the rate of hydrolysis of xylooligomers by xylanase increased with increase in chain length, while beta-glucosidase acted rather slowly on all the oligomers tested. Xylanase exhibited predominant ''endo'' action on xylooligomers attacking the xylan chain at random while beta-glucosidase had ''exo'' action, releasing one xylose residue at a time. On arabinoxylooligomers, however, xylanase exhibited ''exo'' action. Thus, it appears that the presence of the arabinose substituent has, in some way, rendered the terminal xylose-xylose linkage more susceptible to xylanase action. It was also observed that even after extensive hydrolysis with both the enzymes, substantial amounts of the parent arabinoxylooligomer remained unhydrolyzed together with the accumulation of arabinoxylobiose. It can therefore be concluded that the presence of the arabinose substituent in the xylan chain results in linkages that offer resistance to both xylanase and beta-glucosidase action.

Studies on low-intensity oxy-fuel burner

This paper presents experimental and computational results of oxy-fuel burner operating on classical flame and lameless mode for heat release rate of 26 kW/m3. The uniqueness of the burner arises from a slight asymmetric injection of oxygen at near sonic velocities. Measurements of emperature, species, total heat flux, radiative heat flux and NOx emission were carried out inside the furnace and the flow field was computationally analyzed. The flame studies were carried out for coaxial flow of oxygen and fuel jets with similar inlet velocities. This configuration results in slow mixing between fuel and oxygen and the flame is developed at distance away from the burner and the flame is bright/white in colour. In the flameless mode a slight asymmetric injection of the high velocity oxygen jet leads to a large asymmetric recirculation pattern with the recirculation ratio of 25 and the resulting flame is weak bluish in colour with little soot and acetylene formation. The classical flame in comparison is characterised by soot and acetylene formation, higher NOx and noise generation. The distribution of temperature and heat flux in the furnace is more uniform with flameless mode than with flame mode.

Flow pattern analysis in a highly stenotic patient-specific carotid bifurcation model using a turbulence model

The aim of this study is to investigate the blood flow pattern in carotid bifurcation with a high degree of luminal stenosis, combining in vivo magnetic resonance imaging (MRI) and computational fluid dynamics (CFD). A newly developed two-equation transitional model was employed to evaluate wall shear stress (WSS) distribution and pressure drop across the stenosis, which are closely related to plaque vulnerability. A patient with an 80% left carotid stenosis was imaged using high resolution MRI, from which a patient-specific geometry was reconstructed and flow boundary conditions were acquired for CFD simulation. A transitional model was implemented to investigate the flow velocity and WSS distribution in the patient-specific model. The peak time-averaged WSS value of approximately 73Pa was predicted by the transitional flow model, and the regions of high WSS occurred at the throat of the stenosis. High oscillatory shear index values up to 0.50 were present in a helical flow pattern from the outer wall of the internal carotid artery immediately after the throat. This study shows the potential suitability of a transitional turbulent flow model in capturing the flow phenomena in severely stenosed carotid arteries using patient-specific MRI data and provides the basis for further investigation of the links between haemodynamic variables and plaque vulnerability. It may be useful in the future for risk assessment of patients with carotid disease.

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.