An aspect query language model based on query decomposition and high-order contextual term associations

In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.

Automated cross-lingual link discovery in Wikipedia

At NTCIR-9, we participated in the cross-lingual link discovery (Crosslink) task. In this paper we describe our approaches to discovering Chinese, Japanese, and Korean (CJK) cross-lingual links for English documents in Wikipedia. Our experimental results show that a link mining approach that mines the existing link structure for anchor probabilities and relies on the “translation” using cross-lingual document name triangulation performs very well. The evaluation shows encouraging results for our system.

Move it, use it : university-school collaboration for learning to teach physical education in primary schools

Reports of increasing numbers of obese Australian children and adolescents have raised the alarm to be proactive in reducing this so called epidemic. It has evoked a call for greater emphasis on teaching physical education in schools, as a measure for attaining fitness not only with obese students but for all students. This paper emphasises how preservice teachers need to be a key target for implementing physical education (PE) reform in schools, as many primary teachers will be generalists and may not be confident enough to implement PE effectively. Through a review of existing literature, teaching practices essential for the effective promotion and implementation of PE were identified under six broad categories: personal-professional skills development, addressing system requirements, pedagogical practices, managing student behaviour, providing feedback to students, and reflecting on practice. Subsequently, the development of these practices in preservice teachers is considered in the context of a university-school collaboration where preservice teachers taught physical education to primary school students for one day per week over a four week period. These authentic teaching experiences provided the preservice teachers with vital opportunities to put theory into practice and interact with “real-world” students. Self-evaluative data from 38 of these preservice teachers, in the form of a five-part Likert scale survey and extended response survey, demonstrated that they were able to develop the majority of the essential teaching practices identified by literature. In particular, the preservice teachers developed self efficacy, enthusiasm, and motivation for teaching PE, facets which are often found to be lacking in generalist primary teachers and yet are essential if children’s perceptions and habits regarding physical activity are to be changed.

L1 Learning Strategy Instruction does make a difference in EFL listening: An empirical study.

In language learning, listening is the basic skill which learners should begin to develop other skills, namely speaking, reading and writing. This sequence of language learning in most English as Foreign Language (EFL) settings goes against the stream, learning first reading and writing and later listening and speaking. This study investigates the effects of cognitive, process-based approach to instructing EFL listening strategies over 11 weeks during a semester in Persian (L1). Lower intermediate female participants (N = 50) came from a couple of EFL classrooms in an English Language Institute in Iran. The experimental group (n = 25) listened to their classroom activities using a methodology that led learners through four cognitive processes (guessing, making inference, identifying topics and repetition) in Persian was basically successful in EFL listening. The same teacher taught the control group (n = 25), which listened to the same classroom listening activities without any guided attention to the learning strategy process in Persian. A pre and post listening test made by a group of experts in the language institute tracked any development in light of cognitive learning strategy instruction in EFL listening through L1. The hypothesis was that the experimental group received the guided attention in L1 during the classroom listening activities made greater gains and was verified despite the partial improvement of the control group.

Thomas Young’s contributions to geometrical optics

In addition to his work on physical optics, Thomas Young (1773-1829) made several contributions to geometrical optics, most of which received little recognition in his time or since. We describe and assess some of these contributions: Young’s construction (the basis for much of his geometric work), paraxial refraction equations, oblique astigmatism and field curvature, and gradient-index optics.

The internal validity of web-based studies

Honing and Ladinig (2008) make the assertion that while the internal validity of web-based studies may be reduced, this is offset by an increase in external validity possible when experimenters can sample a wider range of participants and experimental settings. In this paper, the issue of internal validity is more closely examined, and it is agued that there is no necessary reason why internal validity of a web-based study should be worse than that of a lab-based one. Errors of measurement or inconsistencies of manipulation will typically balance across conditions of the experiment, and thus need not necessarily threaten the validity of a study’s findings.

Influence of field size on pupil diameter under photopic and mesopic light levels

Purpose: We investigated the interaction between adapting field size and luminance on pupil diameter when cones alone (photopic) or rods and cones (mesopic) were active. Method: Circular achromatic targets (1o to 24o diameter) were presented to eight young participants on a rectangular projector screen. The accommodative influence on pupil diameter was minimized using cycloplegia in the fixing right eye and the consensual pupil reflex was measured in the left eye. Target luminance was adjusted for each stimulus such that corneal flux density (product of field area and luminance) was constant at 3600 cd.deg2m-2 (photopic condition) and 1.49 cd.deg2m-2 (mesopic condition). Results: There were no statistically significant effects of adaptive field size on pupil diameter for either condition. Conclusion: If corneal flux density is kept constant, there will be no change in pupil diameter as the size of the stimulus field increases at either mesopic or photopic lighting levels up to at least 24°.

Hydrothermal synthesis of single crystallin strontium titanate nanocubes

Strontium titanate nanocubes with an average edge length of 150mm have been successfully synthesized from a simple hydrothermal system. Characterization techniques such as X-ray powder diffraction analysis, scanning electron microscopy and energy-dispersive analysis of X-rays were used to investigate the products. The results showed that as-prepared powders are pure SrTiO3 with cubic shape, which consists with the growth habit of its intrinsic crystal structure. These uniform nanocubes with high crystallinity will exhibit superior physical properties in the practical applications. Furthermore, during the experimental process, it has been found that the dilute acid washing process is very important to obtain high pure SrTiO3.

A study on the use of acoustic emission technique as a structural health monitoring tool

As civil infrastructures such as bridges age, there is a concern for safety and a need for cost-effective and reliable monitoring tool. Different diagnostic techniques are available nowadays for structural health monitoring (SHM) of bridges. Acoustic emission is one such technique with potential of predicting failure. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). AEtechnique involves recording the stress waves bymeans of sensors and subsequent analysis of the recorded signals,which then convey information about the nature of the source. AE can be used as a local SHM technique to monitor specific regions with visible presence of cracks or crack prone areas such as welded regions and joints with bolted connection or as a global technique to monitor the whole structure. Strength of AE technique lies in its ability to detect active crack activity, thus helping in prioritising maintenance work by helping focus on active cracks rather than dormant cracks. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. One is the generation of large amount of data during the testing; hence an effective data analysis and management is necessary, especially for long term monitoring uses. Complications also arise as a number of spurious sources can giveAEsignals, therefore, different source discrimination strategies are necessary to identify genuine signals from spurious ones. Another major challenge is the quantification of damage level by appropriate analysis of data. Intensity analysis using severity and historic indices as well as b-value analysis are some important methods and will be discussed and applied for analysis of laboratory experimental data in this paper.

Investigation of cooling energy performance of commercial building in sub-tropical climate through the application of green roof and living wall

This paper investigates cooling energy performance of commercial building before and after green roof and living wall application based on integrated building heat gain model developed from Overall Thermal Transfer Value (OTTV) of building wall and steady state heat transfer process of roof in sub-tropical climate. Using the modelled equation and eQUEST energy simulation tool, commercial building envelope parameters and relevant heat gain parameters have been accumulated to analyse the heat gain and cooling energy consumption of commercial building. Real life commercial building envelope and air-conditioned load data for the sub-tropical climate zone have been collected and compared with the modelled analysis. Relevant temperature data required for living wall and green roof analysis have been collected from experimental setup comprised of both green roof and west facing living wall. Then, Commercial building heat flux and cooling energy performance before and after green roof and living wall application have been scrutinized.

School policy responses to cyberbullying : an Australian legal perspective

The use of electronic means of contact to support repeated aggressive behaviour by an individual or group, that is intended to harm others – or ‘cyberbullying’ as it is now known – is increasingly becoming a problem for modern students, teachers, parents and schools. Increasingly victims of face to face bullying are looking to the law as a means of recourse, not only against bullies but also school authorities who have the legal responsibility to provide a safe environment for learning. It is likely that victims of cyberbullying will be inclined to do the same. This article examines a survey of the anti-bullying policies of a small sample of Australian schools to gauge their readiness to respond to the challenge of cyberbullying, particularly in the context of the potential liability they may face. It then uses that examination as a basis for identifying implications for the future design of school anti-bullying policies.

Solder joint defects classification using the Log-Gabor Filter, the Discrete Wavelet Transform and the Discrete Cosine Transform

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure project quality and reliability. This paper proposes the use of the Log-Gabor filter bank, Discrete Wavelet Transform and Discrete Cosine Transform for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.

On the application of the probabilistic linear discriminant analysis to face recognition across expression

Facial expression is one of the main issues of face recognition in uncontrolled environments. In this paper, we apply the probabilistic linear discriminant analysis (PLDA) method to recognize faces across expressions. Several PLDA approaches are tested and cross-evaluated on the Cohn-Kanade and JAFFE databases. With less samples per gallery subject, high recognition rates comparable to previous works have been achieved indicating the robustness of the approaches. Among the approaches, the mixture of PLDAs has demonstrated better performances. The experimental results also indicate that facial regions around the cheeks, eyes, and eyebrows are more discriminative than regions around the mouth, jaw, chin, and nose.