Mining positive and negative patterns for relevance feature discovery

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. The innovative technique presented in paper makes a breakthrough for this difficulty. This technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. Substantial experiments using this technique on Reuters Corpus Volume 1 and TREC topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and pattern based methods on precision, recall and F measures.

Investigating and theorizing discourse during analogy writing in chemistry

Explanations of the role of analogies in learning science at a cognitive level are made in terms of creating bridges between new information and students’ prior knowledge. In this empirical study of learning with analogies in an 11th grade chemistry class, we explore an alternative explanation at the "social" level where analogy shapes classroom discourse. Students in the study developed analogies within small groups and with their teacher. These classroom interactions were monitored to identify changes in discourse that took place through these activities. Beginning from socio-cultural perspectives and hybridity, we investigated classroom discourse during analogical activities. From our analyses, we theorized a merged discourse that explains how the analog discourse becomes intertwined with the target discourse generating a transitional state where meanings, signs, symbols, and practices are in flux. Three categories were developed that capture how students intertwined the analog and target discourses—merged words, merged utterances/sentences, and merged practices.

Swell : a feature-length screenplay set in the world of Australian surfing, and an accompanying exegesis on three-act structure

Despite many arguments to the contrary, the three-act story structure, as propounded and refined by Hollywood continues to dominate the blockbuster and independent film markets. Recent successes in post-modern cinema could indicate new directions and opportunities for low-budget national cinemas.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

Journalism's screen test

I’ve been researching, teaching and writing about journalism for more than two decades. Throughout that time I’ve used feature films to illustrate howthe journalist is represented in popular culture.

Journalism at the movies

Welcome to the first of what will be a regular review essay on films about journalism, covering recent releases as well as looking back at established classics and under-rated obscurities. And there is plenty to write about. Since 2008, and the end of the research period which informed my 2010 book on Journalists in Film there has been a steady stream of films in which a journalist is a primary character, and in which the nature and functioning of journalism is a theme. Morning Glory (Roger Michell, 2010), the story of a ‘serious’ news man (Harrison Ford) having to adapt to the infotainment environment of breakfast news, came out early in 2011 in the United Kingdom. The well-received UK indie Monsters (Gareth Edwards, 2010), a sci-fi with a journalist at its heart, was released in 2010. In The Soloist (Joe Wright, 2009) Robert Downey Jr played a feature journalist who befriends a mentally ill street musician and seeks to rescue him through his writing. Stieg Larsson’s Millennium trilogy has produced three Swedish films, all of them focused on the campaigning journalist Mikael Blomkvist. The first of these is being remade by Hollywood as of this writing.

Manipulating task constraints to improve tactical knowledge and collective decision-making in rugby union

In team sports such as rugby union, a myriad of decisions and actions occur within the boundaries that compose the performance perceptual- motor workspace. The way that these performance boundaries constrain decision making and action has recently interested researchers and has involved developing an understanding of the concept of constraints. Considering team sports as complex dynamical systems, signifies that they are composed of multiple, independent agents (i.e. individual players) whose interactions are highly integrated. This level of complexity is characterized by the multiple ways that players in a rugby field can interact. It affords the emergence of rich patterns of behaviour, such as rucks, mauls, and collective tactical actions that emerge due to players’ adjustments to dynamically varying competition environments. During performance, the decisions and actions of each player are constrained by multiple causes (e.g. technical and tactical skills, emotional states, plans, thoughts, etc.) that generate multiple effects (e.g. to run or pass, to move forward to tackle or maintain position and drive the opponent to the line), a prime feature in a complex systems approach to team games performance (Bar- Yam, 2004). To establish a bridge between the complexity sciences and learning design in team sports like rugby union, the aim of practice sessions is to prepare players to pick up and explore the information available in the multiple constraints (i.e. the causes) that influence performance. Therefore, learning design in training sessions should be soundly based on the interactions amongst players (i.e.teammates and opponents) that will occur in rugby matches. To improve individual and collective decision making in rugby union, Passos and colleagues proposed in previous work a performer- environment interaction- based approach rather than a traditional performer- based approach (Passos, Araújo, Davids & Shuttleworth, 2008).

Identifying constraints on children with movement difficulties : implications for pedagogues and clinicians

A constraints- based framework for understanding processes of movement coordination and control is predicated on a range of theoretical ideas including the work of Bernstein (1967), Gibson (1979), Newell (1986) and Kugler, Kelso & Turvey (1982). Contrary to a normative perspective that focuses on the production of idealized movement patterns to be acquired by children during development and learning (see Alain & Brisson, 1986), this approach formulates the emergence of movement co- ordination as a function of the constraints imposed upon each individual. In this framework, cognitive, perceptual and movement difficulties and disorders are considered to be constraints on the perceptual- motor system, and children’s movements are viewed as emergent functional adaptations to these constraints (Davids et al., 2008; Rosengren, Savelsbergh & van der Kamp, 2003). From this perspective, variability of movement behaviour is not viewed as noise or error to be eradicated during development, but rather, as essentially functional in facilitating the child to satisfy the unique constraints which impinge on his/her developing perceptual- motor and cognitive systems in everyday life (Davids et al., 2008). Recently, it has been reported that functional neurobiological variability is predicated on system degeneracy, an inherent feature of neurobiological systems which facilitates the achievement of task performance goals in a variety of different ways (Glazier & Davids, 2009). Degeneracy refers to the capacity of structurally different components of complex movement systems to achieve different performance outcomes in varying contexts (Tononi et al., 1999; Edelman & Gally, 2001). System degeneracy allows individuals with and without movement disorders to achieve their movement goals by harnessing movement variability during performance. Based on this idea, perceptual- motor disorders can be simply viewed as unique structural and functional system constraints which individuals have to satisfy in interactions with their environments. The aim of this chapter is to elucidate how the interaction of structural and functional organismic, and environmental constraints can be harnessed in a nonlinear pedagogy by individuals with movement disorders.

An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

User-representative feature selection for keystroke dynamics

Continuous user authentication with keystroke dynamics uses characters sequences as features. Since users can type characters in any order, it is imperative to find character sequences (n-graphs) that are representative of user typing behavior. The contemporary feature selection approaches do not guarantee selecting frequently-typed features which may cause less accurate statistical user-representation. Furthermore, the selected features do not inherently reflect user typing behavior. We propose four statistical based feature selection techniques that mitigate limitations of existing approaches. The first technique selects the most frequently occurring features. The other three consider different user typing behaviors by selecting: n-graphs that are typed quickly; n-graphs that are typed with consistent time; and n-graphs that have large time variance among users. We use Gunetti’s keystroke dataset and k-means clustering algorithm for our experiments. The results show that among the proposed techniques, the most-frequent feature selection technique can effectively find user representative features. We further substantiate our results by comparing the most-frequent feature selection technique with three existing approaches (popular Italian words, common n-graphs, and least frequent ngraphs). We find that it performs better than the existing approaches after selecting a certain number of most-frequent n-graphs.

Attitudinal impact of hybridized writing about a socioscientific issue

The development of scientifically literate citizens remains an important priority of science education; however, growing evidence of students’ disenchantment with school science continues to challenge the realisation of this aim. This triangulation mixed methods study investigated the learning experiences of 152 9th grade students as they participated in an online science-writing project on the socioscientific issue of biosecurity. Students wrote a series of hybridized scientific narratives, or BioStories, that integrate scientific information about biosecurity with narrative storylines. The students completed an online Likert-style questionnaire, the BioQuiz, which examined selected aspects of their attitudes toward science and science learning, prior to their participation in the project, and upon completion of the writing tasks. Statistical analyses of these results and interview data obtained from participating students suggest that hybridized writing about a socioscientific issue developed more positive attitudes toward science and science learning, particularly in terms of the students’ interest and enjoyment. Implications for research and teaching are also discussed.