Differential polarization decoding for robust coherent optical packet switched networks

This paper proposes the use of the 2-D differential decoding to improve the robustness of dual-polarization optical packet receivers and is demonstrated in a wavelength switching scenario for the first time.

Phonics instruction using pseudowords for success in phonetic decoding

This study examined a Pseudoword Phonics Curriculum to determine if this form of instruction would increase students’ decoding skills compared to typical real-word phonics instruction. In typical phonics instruction, children learn to decode familiar words which allow them to draw on their prior knowledge of how to pronounce the word and may detract from learning decoding skills. By using pseudowords during phonics instruction, students may learn more decoding skills because they are unfamiliar with the “words” and therefore cannot draw on memory for how to pronounce the word. It was hypothesized that students who learn phonics with pseudowords will learn more decoding skills and perform higher on a real-word assessment compared to students who learn phonics with real words. ^ Students from two kindergarten classes participated in this study. An author-created word decoding assessment was used to determine the students’ ability to decode words. The study was broken into three phases, each lasting one month. During Phase 1, both groups received phonics instruction using real words, which allowed for the exploration of baseline student growth trajectories and potential teacher effects. During Phase 2, the experimental group received pseudoword phonics instruction while the control group continued real-word phonics instruction. During Phase 3, both groups were taught with real-word phonics instruction. Students were assessed on their decoding skills before and after each phase. ^ Results from multiple regression and multi-level model analyses revealed a greater increase in decoding skills during the second and third phases of the study for students who received the pseudoword phonics instruction compared to students who received the real-word phonics instruction. This suggests that pseudoword phonics instruction improves decoding skills quicker than real-word phonics instruction. This also suggests that teaching decoding with pseudowords for one month can continue to improve decoding skills when children return to real-word phonics instruction. Teacher feedback suggests that confidence with reading increased for students who learned with pseudowords because they were less intimidated by the approach and viewed pseudoword phonics as a game that involved reading “silly” words. Implications of these results, limitations of this study, and areas for future research are discussed. ^

Phonics Instruction using Pseudowords for Success in Phonetic Decoding

This study examined a Pseudoword Phonics Curriculum to determine if this form of instruction would increase students’ decoding skills compared to typical real-word phonics instruction. In typical phonics instruction, children learn to decode familiar words which allow them to draw on their prior knowledge of how to pronounce the word and may detract from learning decoding skills. By using pseudowords during phonics instruction, students may learn more decoding skills because they are unfamiliar with the “words” and therefore cannot draw on memory for how to pronounce the word. It was hypothesized that students who learn phonics with pseudowords will learn more decoding skills and perform higher on a real-word assessment compared to students who learn phonics with real words. Students from two kindergarten classes participated in this study. An author-created word decoding assessment was used to determine the students’ ability to decode words. The study was broken into three phases, each lasting one month. During Phase 1, both groups received phonics instruction using real words, which allowed for the exploration of baseline student growth trajectories and potential teacher effects. During Phase 2, the experimental group received pseudoword phonics instruction while the control group continued real-word phonics instruction. During Phase 3, both groups were taught with real-word phonics instruction. Students were assessed on their decoding skills before and after each phase. Results from multiple regression and multi-level model analyses revealed a greater increase in decoding skills during the second and third phases of the study for students who received the pseudoword phonics instruction compared to students who received the real-word phonics instruction. This suggests that pseudoword phonics instruction improves decoding skills quicker than real-word phonics instruction. This also suggests that teaching decoding with pseudowords for one month can continue to improve decoding skills when children return to real-word phonics instruction. Teacher feedback suggests that confidence with reading increased for students who learned with pseudowords because they were less intimidated by the approach and viewed pseudoword phonics as a game that involved reading “silly” words. Implications of these results, limitations of this study, and areas for future research are discussed.

Decoding Spontaneous Emotional States in the Human Brain.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

Recoding: reprogrammed genetic decoding with an emphasis on antizyme regulatory frameshifting

Recoding embraces mechanisms that augment the rules of standard genetic decoding. The deviations from standard decoding are often purposeful and their realisation provides diverse and flexible regulatory mechanisms. Recoding events such as programed ribosomal frameshifting are especially plentiful in viruses. In most organisms only a few cellular genes are known to employ programed ribosomal frameshifting in their expression. By far the most prominent and therefore well-studied case of cellular +1 frameshifting is in expression of antizyme mRNAs. The protein antizyme is a key regulator of polyamine levels in most eukaryotes with some exceptions such as plants. A +1 frameshifting event is required for the full length protein to be synthesized and this requirement is a conserved feature of antizyme mRNAs from yeast to mammals. The efficiency of the frameshifting event is dependent on the free polyamine levels in the cell. cis-acting elements in antizyme mRNAs such as specific RNA structures are required to stimulate the frameshifting efficiency. Here I describe a novel stimulator of antizyme +1 frameshifting in the Agaricomycotina class of Basidiomycete fungi. It is a nascent peptide that acts from within the ribosome exit tunnel to stimulate frameshifting efficiency in response to polyamines. The interactions of the nascent peptide with components of the peptidyl transferase centre and the protein exit tunnel emerge in our understanding as powerful means which the cell employs for monitoring and tuning the translational process. These interactions can modulate the rate of translation, protein cotranslational folding and localization. Some nascent peptides act in concert with small molecules such as polyamines or antibiotics to stall the ribosome. To these known nascent peptide effects we have added that of a stimulatory effect on the +1 frameshifting in antizyme mRNAs. It is becoming evident that nascent peptide involvement in regulation of translation is a much more general phenomenon than previously anticipated.

ImageLearn - Decoding Britain's Landscape

Abstract Ordnance Survey, our national mapping organisation, collects vast amounts of high-resolution aerial imagery covering the entirety of the country. Currently, photogrammetrists and surveyors use this to manually capture real-world objects and characteristics for a relatively small number of features. Arguably, the vast archive of imagery that we have obtained portraying the whole of Great Britain is highly underutilised and could be ‘mined’ for much more information. Over the last year the ImageLearn project has investigated the potential of "representation learning" to automatically extract relevant features from aerial imagery. Representation learning is a form of data-mining in which the feature-extractors are learned using machine-learning techniques, rather than being manually defined. At the beginning of the project we conjectured that representations learned could help with processes such as object detection and identification, change detection and social landscape regionalisation of Britain. This seminar will give an overview of the project and highlight some of our research results.

Addressing the needs of struggling literacy learners

Think back to your teaching experiences over the past four years. Were there a number of children or adolescents in your classes who seemed to have learning difficulties? What area of their learning seemed to be of greatest concern for these students? Did most of these struggling learners have difficulty with reading? Was expressing their thoughts in writing also a challenge? Did some of these students also have difficulty in listening to and following directions? And did some of these students seem hesitant when asked to speak to the class?

Using Media Technologies in English

English has long been the subject where print text has reigned supreme. Increasingly in our networked and electronically connected world, however, we can be using digital technologies to create and respond to texts studied in English classrooms. The current approach to English includes the concept of ‘multiliteracies,’ which suggests that print texts alone are necessary but not sufficient’ (E.Q, 2000) and that literacy includes the flexible and sustainable mastery of a repertoire of practices. This also includes the decoding and deployment of media technologies (E.Q, 2000). This has become more possible in Australia as secondary students have increasing access to computers and online platforms at home and at school. With the advent of web 2.0., with its interactive platforms and free media making software, teachers and students can use this software to access information and emerging online literature in English covering a range of text types and new forms for authentic audiences and contexts. This chapter is concerned with responding to literary and mediated texts through the use of technologies. If we remain open to trying out new textual forms and see our digital ‘native students’ (Prensky, 2007) as our best resource, we can move beyond technophobia, become digital travellers’ ourselves and embrace new digital forms in our classrooms.

Solving graphics tasks : gender differences in middle-school students

The capacity to solve tasks that contain high concentrations of visual-spatial information, including graphs, maps and diagrams, is becoming increasingly important in educational contexts as well as everyday life. This research examined gender differences in the performance of students solving graphics tasks from the Graphical Languages in Mathematics (GLIM) instrument that included number lines, graphs, maps and diagrams. The participants were 317 Australian students (169 males and 148 females) aged 9 to 12 years. Boys outperformed girls on graphical languages that required the interpretation of information represented on an axis and graphical languages that required movement between two- and three-dimensional representations (generally Map language).

Fast and accurate phonetic spoken term detection

For the first time in human history, large volumes of spoken audio are being broadcast, made available on the internet, archived, and monitored for surveillance every day. New technologies are urgently required to unlock these vast and powerful stores of information. Spoken Term Detection (STD) systems provide access to speech collections by detecting individual occurrences of specified search terms. The aim of this work is to develop improved STD solutions based on phonetic indexing. In particular, this work aims to develop phonetic STD systems for applications that require open-vocabulary search, fast indexing and search speeds, and accurate term detection. Within this scope, novel contributions are made within two research themes, that is, accommodating phone recognition errors and, secondly, modelling uncertainty with probabilistic scores. A state-of-the-art Dynamic Match Lattice Spotting (DMLS) system is used to address the problem of accommodating phone recognition errors with approximate phone sequence matching. Extensive experimentation on the use of DMLS is carried out and a number of novel enhancements are developed that provide for faster indexing, faster search, and improved accuracy. Firstly, a novel comparison of methods for deriving a phone error cost model is presented to improve STD accuracy, resulting in up to a 33% improvement in the Figure of Merit. A method is also presented for drastically increasing the speed of DMLS search by at least an order of magnitude with no loss in search accuracy. An investigation is then presented of the effects of increasing indexing speed for DMLS, by using simpler modelling during phone decoding, with results highlighting the trade-off between indexing speed, search speed and search accuracy. The Figure of Merit is further improved by up to 25% using a novel proposal to utilise word-level language modelling during DMLS indexing. Analysis shows that this use of language modelling can, however, be unhelpful or even disadvantageous for terms with a very low language model probability. The DMLS approach to STD involves generating an index of phone sequences using phone recognition. An alternative approach to phonetic STD is also investigated that instead indexes probabilistic acoustic scores in the form of a posterior-feature matrix. A state-of-the-art system is described and its use for STD is explored through several experiments on spontaneous conversational telephone speech. A novel technique and framework is proposed for discriminatively training such a system to directly maximise the Figure of Merit. This results in a 13% improvement in the Figure of Merit on held-out data. The framework is also found to be particularly useful for index compression in conjunction with the proposed optimisation technique, providing for a substantial index compression factor in addition to an overall gain in the Figure of Merit. These contributions significantly advance the state-of-the-art in phonetic STD, by improving the utility of such systems in a wide range of applications.

Grotesque gestures or sensuous signs? Rethinking notions of apprenticeship in early childhood education

Education might be conceptualized as a swarm of signs. Deleuze, in Proust and Signs (1964/2000) suggests that “Everything that teaches us something emits signs” (p. 4). Such conceptualizations regard education as fluid, multiple and temporal; a young child can display great skill in decoding some signs but not others. Regarding education as temporal and complex operates at some distance to the sociocultural concepts suggested by Vygotsky (1978) which focus on linear sequences of gaining managed, culturally-loaded knowledge from more experienced others. Despite differing theorizations around apprenticeship, during early years education a child becomes sensitive to signs that collectively prioritize conventionalized knowledge acquisition and communication practices. Drawing for learning and communicating exemplifies apprenticeship as a creative process rather than as sequential or culturally driven, and serves to exemplify Deleuzian concepts around the relationships between time and learning, rather than age or development stage and learning.