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.

Scalable document hashing and retrieval

This thesis studies document signatures, which are small representations of documents and other objects that can be stored compactly and compared for similarity. This research finds that document signatures can be effectively and efficiently used to both search and understand relationships between documents in large collections, scalable enough to search a billion documents in a fraction of a second. Deliverables arising from the research include an investigation of the representational capacity of document signatures, the publication of an open-source signature search platform and an approach for scaling signature retrieval to operate efficiently on collections containing hundreds of millions of documents.

MRI-based strain and strain rate analysis of left ventricle: A modified hierarchical transformation model

Background Different from other indicators of cardiac function, such as ejection fraction and transmitral early diastolic velocity, myocardial strain is promising to capture subtle alterations that result from early diseases of the myocardium. In order to extract the left ventricle (LV) myocardial strain and strain rate from cardiac cine-MRI, a modified hierarchical transformation model was proposed. Methods A hierarchical transformation model including the global and local LV deformations was employed to analyze the strain and strain rate of the left ventricle by cine-MRI image registration. The endocardial and epicardial contour information was introduced to enhance the registration accuracy by combining the original hierarchical algorithm with an Iterative Closest Points using Invariant Features algorithm. The hierarchical model was validated by a normal volunteer first and then applied to two clinical cases (i.e., the normal volunteer and a diabetic patient) to evaluate their respective function. Results Based on the two clinical cases, by comparing the displacement fields of two selected landmarks in the normal volunteer, the proposed method showed a better performance than the original or unmodified model. Meanwhile, the comparison of the radial strain between the volunteer and patient demonstrated their apparent functional difference. Conclusions The present method could be used to estimate the LV myocardial strain and strain rate during a cardiac cycle and thus to quantify the analysis of the LV motion function.

Study on the elastic-plastic behavior of a porous hierarchical bioscaffold used for bone regeneration

A perfectly plastic von Mises model is proposed to study the elastic-plastic behavior of a porous hierarchical scaffold used for bone regeneration. The proposed constitutive model is implemented in a finite element (FE) routine to obtain the stress-strain relationship of a uniaxially loaded cube of the scaffold, whose constituent is considered to be composed of cortical bone. The results agree well with experimental data for uniaxial loading case of a cancellous bone. We find that the unhomogenized stress distribution results in different mechanical properties from but still comparable to our previous theory. The scaffold is a promising candidate for bone regeneration.

Disease mapping using Bayesian hierarchical models

description and analysis of geographically indexed health data with respect to demographic, environmental, behavioural, socioeconomic, genetic, and infectious risk factors (Elliott andWartenberg 2004). Disease maps can be useful for estimating relative risk; ecological analyses, incorporating area and/or individual-level covariates; or cluster analyses (Lawson 2009). As aggregated data are often more readily available, one common method of mapping disease is to aggregate the counts of disease at some geographical areal level, and present them as choropleth maps (Devesa et al. 1999; Population Health Division 2006). Therefore, this chapter will focus exclusively on methods appropriate for areal data...

Predicting health programme participation: A gravity‐based, hierarchical modelling approach

Statistical analyses of health program participation seek to address a number of objectives compatible with the evaluation of demand for current resources. In this spirit, a spatial hierarchical model is developed for disentangling patterns in participation at the small area level, as a function of population-based demand and additional variation. For the former, a constrained gravity model is proposed to quantify factors associated with spatial choice and account for competition effects, for programs delivered by multiple clinics. The implications of gravity model misspecification within a mixed effects framework are also explored. The proposed model is applied to participation data from a no-fee mammography program in Brisbane, Australia. Attention is paid to the interpretation of various model outputs and their relevance for public health policy.

A multi-hierarchical strategy for on-ramp coordination

Ramp metering (RM) is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, RM algorithms fall into two categories by their effective scope: local control and coordinated control. Local control algorithm determines the metering rate based on the traffic condition on adjacent motorway mainline and the on-ramp. Conversely, coordinated RM strategies make use of measurements from the entire motorway network to operate individual ramp signals for optimal performance at the network level. This study proposes a multi-hierarchical strategy for on-ramp coordination. The strategy is structured in two layers. At the higher layer, a centralised, predictive controller plans the coordination control within a long update interval based on the location of high-risk breakdown flow. At the lower layer, reactive controllers determine the metering rates of those ramps involved in the ramp coordination with a short update interval. This strategy is modelled and applied to the northbound model of the Pacific Motorway in a micro-simulation platform (AIMSUN). The simulation results show that the proposed strategy effectively delays the onset of congestion and reduces total congestion with better managed on-ramp queues.

The dynamics of individual teacher autonomy: A case study of teachers' work in a Queensland secondary school

The emphasis on collegiality and collaboration in the literature on teachers' work and school reform has tended to underplay the significance of teacher autonomy. This thesis explores the dynamics of teachers' understandings and experiences of individual teacher autonomy (as contrasted with collective autonomy) in an independent school in Queensland which promoted itself as a 'teachers' school' with a strong commitment to individual teacher autonomy. The research was a case study which drew on methodological signposts from critical, feminist and traditional ethnography. Intensive fieldwork in the school over five months incorporated the ethnographic techniques of observation, interviews and document analysis. Teachers at Thornton College understood their experience of individual autonomy at three interrelated levels--in terms of their work in the classroom, their working life in the school, and their voice in the decision-making processes of the school. They felt that they experienced a great deal of individual autonomy at each of these three levels. These understandings and experiences of autonomy were encumbered or enabled by a range of internal and external stakeholder groups. There were also a number of structural influences (community perceptions, market forces, school size, time and bureaucracy) emerging from the economic, social and political structures in Australian society which influenced the experience of autonomy by teachers. The experience of individual teacher autonomy was constantly shifting, but there were some emergent patterns. Consensus on educational goals and vision, and strong expressions of trust and respect between teachers and stakeholders in the school, characterised the contexts in which teachers felt they experienced high levels of autonomy in their work. The demand for accountability and desire for relatedness motivated stakeholders and structural forces to influence teacher autonomy. Some significant gaps emerged between the rhetoric of a commitment to individual teacher autonomy and decision-making practices in the school, that gave ultimate power to the co-principals. Despite the rhetoric and promotion of non-hierarchical structures and collaborative decision-making processes, many teachers perceived that their experience of individual autonomy remained subject to the exercise of 'partial democracy' by school leaders.

Framing as status or benefits? Consumers’ reactions to hierarchical loyalty program communication

Purpose A fundamental aspect of hierarchical loyalty programs is that some consumers get rewards that others do not. Despite the widespread use of such programs, academics have long debated whether these benefits are outweighed by the potential negative impact of the differential treatment of customers. This study extends our understanding, examining the impact of message framing on consumers’ reactions to hierarchical loyalty structures. Design/methodology/approach Three online studies were conducted. Study 1 uses advertisements to manipulate the message frame’s emphasis (benefits vs. status). Study 2 manipulates consumers’ frame of thought by directing their attention to either changes in benefits or status. Finally, Study 3 uses the proposed framework to reconcile contradictory findings from past research. Findings Low-frequency customers who do not expect to qualify for a superior customer tier tend to reject hierarchical programs when thinking about status. In contrast, when these customers think about concrete rewards, loyalty program messages produce no negative reactions. High-frequency customers are positively affected by communication regardless of the type of benefits framed. Research limitations/implications All studies were done online potentially limiting the external validity of the results. Nevertheless, the impact of message framing on perceptions about the loyalty program seems to be quite robust across different studies and manipulations. Practical implications When communicating with low-frequency customers managers should avoid promising status; customers should instead be motivated based on concrete rewards. High-frequency customers are indifferent to alternative emphasis of communication frames. Originality/value Marketing academics have acknowledged the importance of being able to reward top customers without demotivating light and moderate users. Our research is the first to provide a solution to this issue.

A flexible hierarchical approach for facial age estimation based on multiple features

Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

Parents as co-researchers at home: Using an observational method to document young children’s use of technology

This paper discusses the use of observational video recordings to document young children’s use of technology in their homes. Although observational research practices have been used for decades, often with video-based techniques, the participant group in this study (i.e., very young children) and the setting (i.e., private homes), provide a rich space for exploring the benefits and limitations of qualitative observation. The data gathered in this study point to a number of key decisions and issues that researchers must face in designing observational research, particularly where non-researchers (in this case, parents) act as surrogates for the researcher at the data collection stage. The involvement of parents and children as research videographers in the home resulted in very rich and detailed data about children’s use of technology in their daily lives. However, limitations noted in the dataset (e.g., image quality) provide important guidance for researchers developing projects using similar methods in future. The paper provides recommendations for future observational designs in similar settings and/or with similar participant groups.

Mining topical relevant patterns for multi-document summarization

Multi-document summarization addressing the problem of information overload has been widely utilized in the various real-world applications. Most of existing approaches adopt term-based representation for documents which limit the performance of multi-document summarization systems. In this paper, we proposed a novel pattern-based topic model (PBTMSum) for the task of the multi-document summarization. PBTMSum combining pattern mining techniques with LDA topic modelling could generate discriminative and semantic rich representations for topics and documents so that the most representative and non-redundant sentences can be selected to form a succinct and informative summary. Extensive experiments are conducted on the data of document understanding conference (DUC) 2007. The results prove the effectiveness and efficiency of our proposed approach.

Carbon-coated hierarchical SnO2 hollow spheres for lithium ion batteries

Hierarchical SnO2 hollow spheres self-assembled from nanosheets were prepared with and without carbon coating. The combination of nanosized architecture, hollow structure, and a conductive carbon layer endows the SnO2-based anode with improved specific capacity and cycling stability, making it more promising for use in lithium ion batteries.

3D hierarchical rutile TiO2 and metal-free organic sensitizer producing dye-sensitized solar cells 8.6% conversion efficiency

Three-dimensional (3D) hierarchical nanoscale architectures comprised of building blocks, with specifically engineered morphologies, are expected to play important roles in the fabrication of 'next generation' microelectronic and optoelectronic devices due to their high surface-to-volume ratio as well as opto-electronic properties. Herein, a series of well-defined 3D hierarchical rutile TiO2 architectures (HRT) were successfully prepared using a facile hydrothermal method without any surfactant or template, simply by changing the concentration of hydrochloric acid used in the synthesis. The production of these materials provides, to the best of our knowledge, the first identified example of a ledgewise growth mechanism in a rutile TiO2 structure. Also for the first time, a Dye-sensitized Solar Cell (DSC) combining a HRT is reported in conjunction with a high-extinction-coefficient metal-free organic sensitizer (D149), achieving a conversion efficiency of 5.5%, which is superior to ones employing P25 (4.5%), comparable to state-of-the-art commercial transparent titania anatase paste (5.8%). Further to this, an overall conversion efficiency 8.6% was achieved when HRT was used as the light scattering layer, a considerable improvement over the commercial transparent/reflector titania anatase paste (7.6%), a significantly smaller gap in performance than has been seen previously.

Robust superhydrophobicity of hierarchical ZnO hollow microspheres fabricated by two-step self-assembly

Superhydrophobic and superhydrophilic surfaces have been extensively investigated due to their importance for industrial applications. It has been reported, however, that superhydrophobic surfaces are very sensitive to heat, ultraviolet (UV) light, and electric potential, which interfere with their long-term durability. In this study, we introduce a novel approach to achieve robust superhydrophobic thin films by designing architecture-defined complex nanostructures. A family of ZnO hollow microspheres with controlled constituent architectures in the morphologies of 1D nanowire networks, 2D nanosheet stacks, and 3D mesoporous nanoball blocks, respectively, was synthesized via a two-step self-assembly approach, where the oligomers or the constituent nanostructures with specially designed structures are first formed from surfactant templates, and then further assembled into complex morphologies by the addition of a second co-surfactant. The thin films composed of two-step synthesized ZnO hollow microspheres with different architectures presented superhydrophobicities with contact angles of 150°-155°, superior to the contact angle of 103° for one-step synthesized ZnO hollow microspheres with smooth and solid surfaces. Moreover, the robust superhydrophobicity was further improved by perfluorinated silane surface modification. The perfluorinated silane treated ZnO hollow microsphere thin films maintained excellent hydrophobicity even after 75 h of UV irradiation. The realization of environmentally durable superhydrophobic surfaces provides a promising solution for their long-term service under UV or strong solar light irradiations.